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Below is the List of Distinguished Final Year 100+ Machine Learning Projects Ideas or suggestions for Final Year students you can complete any of them or expand them into longer projects if you enjoy them.Nonlinear Reconstruction of Genetic Networks Implicated in AML.Aaron Goebel, Mihir Mongia .[pdf]Can Machines Learn Genres.Aaron Kravitz, Eliza Lupone, Ryan Diaz.[pdf]Identifying Gender From Facial Features.Abhimanyu Bannerjee, Asha Chigurupati.[pdf]Equation to LaTeX.Abhinav Rastogi, Sevy Harris.[pdf]Intensity prediction using DYFI.Abhineet Gupta.[pdf]Artificial Intelligence on the Final Frontier – Using Machine Learning to Find New Earths.Abraham Botros.[pdf]Life Expectancy Post Thoracic Surgery.Adam Abdulhamid, Ivaylo Bahtchevanov, Peng Jia.[pdf]Making Sense of the Mayhem- Machine Learning and March Madness.Adam Ginzberg, Alex Tran.[pdf]Better Reading Levels through Machine Learning.AdamGall.[pdf]What are People Saying about Net Neutrality.Adison Wongkar, Christoph Wertz.[pdf]Bird Species Identification from an Image.Aditya Bhandari, Ameya Joshi, Rohit Patki.[pdf]Stay Alert.Aditya Sarkar, Quentin Perrot, Julien Kawawa.[pdf]A bigram extension to word vector representation.Adrian Sanborn, Jacek Skryzalin.[pdf]Mining for Confusion – Classifying Affect in MOOC Learners’ Discussion Forum Posts.Akshay Agrawal, Shane Leonard.[pdf]Cardiac Arrhythmias Patients.AlGharbi Fatema, Fazel Azar, Haider Batool.[pdf]Prediction of Average and Perceived Polarity in Online Journalism.Albert Chu, Kensen Shi, Catherine Wong.[pdf]Cardiac Dysrhythmia Detection with GPU-Accelerated Neural Networks.Albert Haque.[pdf]Nicolas Sanchez Ruck Those Stats!.Alejandro Sanchez.[pdf]Classifying Wikipedia People Into Occupations.Aleksandar Gabrovski.[pdf]Classification of Soil Contamination.Aleo Mok.[pdf]Automated Essay Grading.Alex Adamson, Andrew Lamb, Ralph Ma.[pdf]Relative and absolute equity return prediction using supervised learning.Alex Alifimoff, Axel Sly.[pdf]Seizure Prediction from Intracranial EEG Recordings.Alex Fu, Spencer Gibbs, Yuqi Liu.[pdf]Predicting Seizure Onset with Intracranial Electroencephalogram(EEG) Data.Alex Greaves, Arushi Raghuvanshi, Kai-Yuan Neo.[pdf]Classifying Complex Legal Documents.Alex Ratner.[pdf]Machine Learning Applied to the Detection of Retinal Blood Vessels.Alex Yee.[pdf]Survival Outcome Prediction for Cancer Patients.Alexander Herrmann .[pdf]Predicting Cellular Link Failures to Improve User Experience on Smartphones.Alexander Tom, Srini Vasudevan.[pdf]Yelp Personalized Reviews.Alexis Weill, Thomas Palomares, Arnaud Guille.[pdf]KMeansSL.Alfred Xue, Colin Wei.[pdf]Strength in numbers_ Modelling the impact of businesses on each other.Amir Sadeghian, Hakan Inan, Andres Noetzli.[pdf]Correlation Based Multi-Label Classification.Amit Garg, Jonathan Noyola, Romil Verma.[pdf]Landmark Recognition Using Machine Learning.Andrew Crudge, Will Thomas, Kaiyuan Zhu.[pdf]CarveML an application of machine learning to file fragment classification.Andrew Duffy.[pdf]rClassifier.Andrew Giel,Jon NeCamp,HussainKader.[pdf]Using Vector Representations to Augment Sentiment Analysis Training Data.Andrew McLeod, Lucas Peeters.[pdf]What Project Should I Choose.Andrew Poon.[pdf]Analyzing Vocal Patterns to Determine Emotion.Andy Sun, Maisy Wieman.[pdf]Predicting the Commercial Success of Songs Based on Lyrics and Other Metrics.Angela Xue, Nick Dupoux.[pdf]Application Of Machine Learning To Aircraft Conceptual Design.Anil Variyar.[pdf]Extracting Word Relationships from Unstructured Data.Anirudha Bhat, Krithika Iyer, Rahul Venkatraj.[pdf]Machine Learning for Predicting Delayed Onset Trauma Following Ischemic Stroke.Anthony Ma, Gus Liu.[pdf]Classifying Online User Behavior Using Contextual Data.Anunay Kulshrestha, Akshay Rampuria, Aditya Ramakrishnan.[pdf]Real Time Flight Path Optimization Under Constraints Using Surrogate Flutter Function.Arthur Paul-Dubois-Taine.[pdf]Real-Time Dense Map Matching with Naive Hidden Markov Models Delay versus Accuracy.Arun Jambulapati, Juhana Kangaspunta, Youssef Ahres, Loek Janssen.[pdf]Prediction Function from Sequence in Venom Peptide Families.Arvind Kannan, G. Seshadri.[pdf]Restaurant Recommendation System.Ashish Gandhe.[pdf]Home Electricity Load Forecasting.Atinuke Ademola Idowu, Pawel Kupsc, Sonya Mollinger.[pdf]Learning Dota 2 Team Compositions.Atish Agarwala, Michael Pearce.[pdf]Applying Deep Learning to derive insights about non-coding regions of the genome.Avanti Shrikumar, Anna Saplitski, Sofia Luna Frank-Fischer.[pdf]Classification of Higgs Jets as Decay Products of a Randall-Sundrum Graviton at the ATLAS Experiment.Aviv Cukierman, Zihao Jiang.[pdf]SemenFertilityPrediction.Axel Guyon,Florence Koskas,Yoann Buratti.[pdf]Sentiment Analysis Using Semi-Supervised Recursive Autoencoders and Support Vector Machines.Bahareh Ghiyasian, Yun Fei Guo.[pdf]Classifying Syllables in Imagined Speech using EEG Data.Barak Oshri, Nishith Khandwala, Manu Chopra.[pdf]Abraham Starosta-Typeguess.Baris Akis, Mariano Sorgente.[pdf]Predicting Usefulness of Yelp Reviews.Ben Isaacs, Xavier Mignot, Maxwell Siegelman.[pdf]Predicting Soccer Results in the English Premier League.Ben Ulmer, Matt Fernandez.[pdf]Detecting Heart Abnormality using ECG with CART.Ben Zhou, Gaspar Garcia, Paurakh Rajbhandary.[pdf]Down and Dirty with Data.Bharat Arora, Roger Davidson, Christopher Wildman.[pdf]Hierarchical Classification of Amazon Products.Bin Wang, Shaoming Feng.[pdf]Predicting high-risk countries for political instability and conflict.Blair Huffman, Emma Marriott, April Yu.[pdf]Machine Learning Implementation in live-cell tracking.Bo Gu.[pdf]Any Given Sunday.Bobak Moallemi, Matthew Wilson, Steven Hoerning.[pdf]P300 Error Detection.Boyeaux Felix,Chatoor Nehan.[pdf]Automated Canvas Analysis for Painting Conservation.Brendan Tobin.[pdf]Office Appliance Classification.Brock Petersen, Gerrit de Moor, Elissa Goldner.[pdf]Sentiment Analysis on Movie Reviews.Cai Xiao, Ya Wang.[pdf]Predicting Mobile Application Success.Cameron Tuckerman.[pdf]Modeling Activity Recognition Using Physiological Data Collected from Wearable Technology.Cezanne Camacho, Jennifer Li, Jeffrey Yang.[pdf]Neural Network Joint Language Model.Charles Qi.[pdf]Yelp Recommendation System Using Advanced Collaborative Filtering.Chee Hoon Ha.[pdf]Prediction of Yelp Review Star Rating using Sentiment Analysis.Chen Li, Jin Zhang.[pdf]Classification of Bad Accounts in Credit Card Industry.Chengwei Yuan.[pdf]Classification Of Musical Playing Styles.Chet Gnegy.[pdf]Email Filtering By Response Required.Chris Knight.[pdf]Forecasting Utilization in City Bike-Share Program.Christina Lee, David Wang, Adeline Wong.[pdf]Recommender.Christopher Aberger.[pdf]Predicting Cell Type-Specific Chromatin States from Genetic Regulatory Networks.Christopher Probert, Anthony Ho.[pdf]Pose Estimation Based on 3D Models.Chuiwen Ma, Liang Shi.[pdf]Visual Localization and POMDP for Autonomous Indoor Navigation.Chulhee Yun, Sungjoon Choi.[pdf]Contours and Kernels-The Art of Sketching.Dan Guo,Paula Kusumaputri,Amani Peddada.[pdf]Indoor Positioning System Using Wifi Fingerprint.Dan Li, Le Wang, Shiqi Wu.[pdf]Predicting air pollution level in a specific city.Dan Wei.[pdf]Prediction of Transcription Factors that Regulate Common Binding Motifs.Dana Wyman, Emily Alsentzer.[pdf]Multi-class motif discovery in keratinocyte differentiation.Daniel Kim.[pdf]Defensive Unit Performance Analysis.Daniel ONeel, Reed Johnson.[pdf]Diagnosing Malignant versus Benign Breast Tumors via Machine Learning Techniques in High Dimensions.Danielle Maddix.[pdf]Hacking the Hivemind.Daria Lamberson,Leo Martel, Simon Zheng.[pdf]Diagnosing Parkinson’s from Gait.Daryl Chang, Marco Alban-Hidalgo, Kevin Hsu.[pdf]Implementing Machine Learning Algorithms on GPUs for Real-Time Traffic Sign Classification.Dashiell Bodington, Eric Greenstein, Matthew Hu.[pdf]Vignette.David Eng, Andrew Lim, Pavitra Rengarajan.[pdf]Machine Learning In JavaScript.David Frankl.[pdf]Searching for exoplanets in the Kepler public data.David Glass, Xiaofan Jin.[pdf]Model Clustering via Group Lasso.David Hallac.[pdf]Improving Positron Emission Tomography Imaging with Machine Learning.David Hsu.[pdf]Algorithmic Trading of Futures via Machine Learning.David Montague.[pdf]Topic based comments exploration for online articles.Deepak Zambre, Ajey Shah.[pdf]Personal Legal Counselor and Interpreter of the Law via Machine Learning.Derek Yan, Tianyi Wang, Patrick Chase.[pdf]Personalized Web Search.Dhanraj Mavilodan, Kapil Jaisinghani, Radhika Bansal.[pdf]Detecting Ads in a Machine Learning Approach.Di Zhang.[pdf]Predicting Mitochondrial tRNA Modification.Diego Calderon.[pdf]Collaborative Neighborhoods.Diego Represas, David Dindi.[pdf]Estimation of Causal Effects from Observational Study of Job Training Program.Dmitry Arkhangelsky, Rob Donnelly.[pdf]Deep Leraning Architecture for Univariate Time Series Forecasting.Dmitry Vengertsev.[pdf]Solomon.Do Kwon, Gyujin Oh, Ki Suk Jang, Ji Park.[pdf]Automatic detection of nanoparticles in tissue sections.Dor Shaviv, Orly Liba.[pdf]Implementation of Deep Convolutional NeuralNet on a DSP.Elaina Chai.[pdf]Evergreen or Ephemeral – Predicting Webpage Longevity Through Relevancy Features.Elaine Zhou, Lingtong Sun.[pdf]MacMalware.Elizabeth Walkup.[pdf]Extractive Fiction Summarization Using Sentence Significance Scoring Models.Eric Holmdahl, Ashkon Farhangi, Lucio Tan.[pdf]Identifying And Predicting Market Reactions To Information Shocks In Commodity Markets.Eric Liu, Vedant Ahluwalia, Deepyaman Datta, Dongyang Zhang.[pdf]An EM-Derived Approach to Blind HRTF Estimation.Eric Schwenker.[pdf]The Many Dimensions of Net Neutrality.Erin Antono, Deger Turan, Justine Zhang.[pdf]Learning To Predict Dental Caries For Preschool Children.Fangzhou Guo, Huaiyang Zhong, Yuchen Li.[pdf]Information based feature selection.Farzan Farnia, Abbas Kazerouni, Afshin Babveyh.[pdf]Identifying Elephant Vocalizations.Flavia Crisrtina Grey Rodriguez, Sergio Patricio Figueroa Sanz.[pdf]Predicting Protein Fragment Binding.Flynn Wu.[pdf]Bike Share Usage Prediction in London.Ford Rylander, Bo Peng, Jeff Wheeler.[pdf]Localized Explicit Semantic Analysis.Francis Lewis.[pdf]Robo Brain Massive Knowledge Base for Robots.Gabriel Kho, Christina Hung, Hugh Cunningham.[pdf]Understanding Music Genre Similarity.Gabriela Groth.[pdf]Correlated Feature Selection for Single-Cell Phenotyping.Geoff Stanley.[pdf]Activity Recognition in Construction Sites Using 3D Accelerometer and Gyrometer.Gustavo Cezar .[pdf]Event-based stock market prediction.Hadi Pouransari, Hamid Chalabi.[pdf]Recommendation Based On User Experience.Hai Vu.[pdf]Spectrum Adaptation in Multicarrier Interference Channels.Haleema Mehmood.[pdf]Exploring Potential for Machine Learning on Data About K-12 Teacher Professional Development.Hamilton Plattner.[pdf]Player Behavior and Optimal Team Compositions for Online Multiplayer Games.Hao Yi Ong, Sunil Deolalikar, Mark Peng.[pdf]Algorithmic Trading Strategy Based On Massive Data Mining.Haoming Li, Tianlun Li, Zhijun Yang.[pdf]Face Detection And Recognition Of Drawn Characters.Herman Chau.[pdf]Gene Expression Analysis Of HCMV Latent Infection.Hie Hong.[pdf]A New Kalman Filter Method.Hojat Ghorbanidehno, Hee Sun Lee.[pdf]Using Tweets for single stock price prediction.Hongshan Chu, Ye Tian, Hongyuan Yuan.[pdf]Classification of Human Posture and Movement Using Accelerometer Data.Huafei Wang, Jennifer Wu.[pdf]Naïve Bayes Classifier And Profitability of Options Gamma Trading.HyungSup Lim.[pdf]Vector-based Sentiment Analysis of Movie Reviews.Ian Roberts, Lisa Yan.[pdf]A General-Purpose Sentence-Level Nonsense Detector.Ian Tenney.[pdf]Characterizing Genetic Variation in Three Southeast Asian Populations.Ilana Arbisser, Jonathan Kang.[pdf]Machine Learning for the Smart Grid.Iliana Voynichka.[pdf]Predicting Africa Soil Properties.Iretiayo Akinola, Thomas Dowd.[pdf]Automated Bitcoin Trading via Machine Learning Algorithms.Isaac Madan, Shaurya Saluja, Aojia Zhao.[pdf]SkatBot.Ivan Leung, Pedro Milani, Ben-han Sung.[pdf]Tradeshift Text Classification.Jacob Conrad Trinidad, Ian Torres.[pdf]New York City Bike Share.James Kunz, Everett Yip, Gary Miguel.[pdf]Predicting Seizure Onset in Epileptic Patients Using Intercranial EEG Recordings.Janet An, Amy Bearman, Catherine Dong.[pdf]Predicting Foster Care Exit.Jason Huang.[pdf]Yelp Recommendation System.Jason Ting, Swaroop Indra Ramaswamy.[pdf]Predicting National Basketball Association Game Winners.Jasper Lin, Logan Short, Vishnu Sundaresan.[pdf]Predicting Yelp Ratings From Business and User Characteristics.Jeff Han, Justin Kuang, Derek Lim.[pdf]Predicting Popularity of Pornography Videos.Jessie Duan.[pdf]Accurate Campaign Targeting Using Classification Algorithms.Jieming Wei, Sharon Zhang.[pdf]Forecasting Bike Rental Demand.Jimmy Du, Rolland He, Zhivko Zhechev.[pdf]Predicting User Following Behavior On Tencent Weibo.Jinfeng Huang, Hai Huang, Zhaoyang Jin .[pdf]Improving Taxi Revenue With Reinforcement Learning.Jingshu Wang, Benjamin Lampert.[pdf]Learning Facial Expressions From an Image.Jithin Thomas, Bhrugurajsinh Chudasama, Chinmay Duvedi.[pdf]All Your Base Are Belong To Us English Texts Written by Non-Native Speakers.Joanna Kim, Jonathan Hung.[pdf]Identifying Regions High Turbidity.Joe Adelson.[pdf]A Comparison of Classification Methods for Expression Quantitative Trait Loci.Joe Davis.[pdf]Predicting Mobile Users Future Location.John Doherty .[pdf]Machine Learning Madness.John Gold, Elliot Chanen.[pdf]Semi-Supervised Learning For Sentiment Analysis.John Miller, Aran Nayebi, Amr Mohamed.[pdf]Legal Issue Spotting.John Phillips.[pdf]A novel way to Soccer Match Prediction.Jongho Shin, Robert Gasparyan.[pdf]Morphological Galaxy Classification.Jordan Duprey, James Kolano.[pdf]Predicting Helpfulness Ratings of Amazon Product Reviews.Jordan Rodak, Minna Xiao, Steven Longoria.[pdf]Predicting Course Completions For Online Courses.Joseph Paetz.[pdf]An Adaptive System For Standardized Test Preparation.Julia Enthoven.[pdf]Single Molecule Biophysics Machine Learning For Automated Data Processing.Junhong Choi, Soomin Cho.[pdf]Understanding Comments Submitted to FCC on Net Neutrality.Junhui Mao, Jing Xia, Woncheol Jeong.[pdf]Direct Data-Driven Methods for Decision Making under Uncertainty.Junjie Qin.[pdf]From Food To Wine.Justin Meier.[pdf]Classifying Legal Questions into Topic Areas Using Machine Learning.Karthik Jagadeesh, Brian Lao.[pdf]Predicting Hit Songs with MIDI Musical Features.Kedao Wang.[pdf]Machine Learning Methods for Biological Data Curation.Kelley Paskov.[pdf]Classifying Forest Cover Type using Cartographic Features.Kevin Crain, Graham Davis.[pdf]Peer Lending Risk Predictor.Kevin Tsai,Sivagami Ramiah,Sudhanshu Singh.[pdf]Learning Distributed Representations of Phrases.Konstantin Lopyrev.[pdf]Estimation Of Word Representations Using Recurrent Neural Networks And Its Application In Generating Business Fingerprints.Kuan Fang.[pdf]Gender Identification by Voice.Kunyu Chen.[pdf]Applications Of Machine Learning To Predict Yelp Ratings.Kyle Carbon, Kacyn Fujii, Prasanth Veerina.[pdf]Methodology for Sparse Classification Learning Arrhythmia.Lee Tanenbaum.[pdf]Predicting March Madness.Levi Franklin.[pdf]Net Neutrality Language Analysis.Li Tao, Xinyi Xie.[pdf]Characterizing Atrial Fibrillation Burden for Stroke Prevention.Lichy Han.[pdf]Predict Seizures in Intracranial EEG Recordings.Linyu He, Lingbin Li.[pdf]Automated Music Track Generation.Louis Eugene, Guillaume Rostaing.[pdf]Characterizing Overlapping Galaxies.Luis Alvarez.[pdf]Understanding Player Positions in the NBA.Luke Lefebure.[pdf]Cross-Domain Product Classification with Deep Learning.Luke de Oliveira, Alfredo Lainez, Akua Abu.[pdf]Predicting Heart Attacks.Luyang Chen, Qi Cao, Sihua Li, Xiao Ju.[pdf]Prediction of Bike Sharing Demand for Casual and Registered Users.Mahmood Alhusseini.[pdf]Classification Of Arrhythmia Using ECG Data.Manas Karandikar, Giulia Guidi.[pdf]What Can You Learn From Accelerometer Data.Manikantan Shila.[pdf]Speaker Recognition for Multi-Source Single-Channel Recordings.Maria Frank, Neil Gallagher, Jose Kruse Perin.[pdf]Prediction of consumer credit risk.Marie-Laure Charpignon, Enguerrand Horel, Flora Tixier.[pdf]Machine Learning for Network Intrusion Detection.Martina Troesch, Ian Walsh.[pdf]Predicting Paper Counts in the Biological Sciences.Matt Denton, Jose Hernandez, Debnil Sur.[pdf]Prediction of Price Increase for MTG Cards.Matt Pawlicki, Joe Polin, Jesse Zhang.[pdf]Twitter Classification into the Amazon Browse Node Hierarchy.Matthew Long, Jiao Yu, Anshul Kundani.[pdf]Determining Mood From Facial Expressions.Matthew Wang, Spencer Yee.[pdf]Visualizing Personalized Cancer Risk Prediction.Maulik Kamdar.[pdf]Predicting the Total Number of Points Scored in NFL Games.Max Flores, Ajay Sohmshetty.[pdf]Short Term Power Forecasting Of Solar PV Systems Using Machine Learning Techniques.Mayukh Samanta,Bharath Srikanth,Jayesh Yerrapragada.[pdf]Star-Galaxy Separation in the Era of Precision Cosmology.Michael Baumer, Noah Kurinsky, Max Zimet.[pdf]Artist Attribution via Song Lyrics.Michael Mara.[pdf]Accelerometer Gesture Recognition.Michael Xie, David Pan.[pdf]Arrythmia Classification for Heart Attack Prediction.Michelle Jin.[pdf]#ML#NLP-Autonomous Tagging Of Stack Overflow Posts.Mihail Eric, Ana Klimovic, Victor Zhong.[pdf]Scheduling Tasks Under Constraints.Mike Yu,Dennis Xu,Kevin Moody.[pdf]Classification Of Beatles Authorship.Miles Bennett, Casey Haaland, Atsu Kobashi.[pdf]Classification of Accents of English Speakers by Native Language.Morgan Bryant, Amanda Chow, Sydney Li.[pdf]Exposing commercial value in social networks matching online communities and businesses.Murali Narasimhan, Camelia Simoiu, Anthony Ward.[pdf]Hacking the genome.Namrata Anand.[pdf]How Hot Will It Get Modeling Scientific Discourse About Literature.Natalie Telis.[pdf]Permeability Prediction of 3-D Binary Segmented Images Using Neural Networks.Nattavadee Srisutthiyakorn.[pdf]Automated Identification of Artist Given Unknown Paintings and Quantification of Artistic Style.Nicholas Dufour, Kyle Griswold, Michael Lublin.[pdf]Predicting Lecture Video Complexity.Nick Su, Ismael Menjivar.[pdf]Result Prediction of Wikipedia Administrator Elections based ondNetwork Features.Nikhil Desai, Raymond Liu, Catherine Mullings.[pdf]Predicting The Treatment Status.Nikolay Doudchenko.[pdf]Error Detection based on neural signals.Nir Even-Chen, Igor Berman.[pdf]Speech Similarity.OReilly Mavrommatis.[pdf]Data-Driven Modeling and Control of an Autonomous Race Car.Ohiremen Dibua, Aman Sinha, and John Subosits.[pdf]Predicting the Diagnosis of Type 2 Diabetes Using Electronic Medical Records.Oliver Bear Dont Walk IV, David Joosten, Tim Moon.[pdf]A Novel Approach to Predicting the Results of NBA Matches.Omid Aryan, Ali Reza Sharafat.[pdf]Automatically Generating Musical Playlists.Paul Martinez.[pdf]Solar Flare Prediction.Paul Warren,Gabriel Bianconi.[pdf]Application of machine learning techniques for well pad identification inathe Bakken oil fielda.Philip Brodrick, Jacob Englander.[pdf]Anomaly Detection in Bitcoin Network Using Unsupervised Learning Methods.Phillip Pham,Steven Li.[pdf]Two-step Semi-supervised Approach for Music Structural Classificiation.Prateek Verma, Yang-Kai Lin, Li-Fan Yu.[pdf]Domain specific sentiment analysis using cross-domain data.Praveen Rokkam, Marcello Hasegawa.[pdf]Instrumental Solo Generator.Prithvi Ramakrishnan, Aditya Dev Gupta.[pdf]Cross-Domain Text Understanding in Online SocialData.Qian Lin, Shenxiu Liu, Zhao Yang.[pdf]From Paragraphs to Vectors and Back Again.Qingping He.[pdf]HandwritingRecognition.Quan Nguyen, Maximillian Wang, Le Cheng Fan.[pdf]Chemical Identification with Chemical Sensor Arrays.Quintin Stedman.[pdf]Genre Classification Using Graph Representations of Music.Rachel Mellon, Dan Spaeth, Eric Theis.[pdf]Collaborative Filtering Recommender Systems.Rahul Makhijani, Saleh Samaneh, Megh Mehta.[pdf]Detecting The Direction Of Sound With A Compact Microphone Array.Rajewski.[pdf]Finding Undervalued Stocks With Machine Learning.Ramneet Rekhi, Huan Wei, Tucker Ward, Michael Downs.[pdf]Multilevel Local Search Algorithms for Modularity Clustering.Randolf Rotta, Andreas Noack.[pdf]Automated Detection and Classification of Cardiac Arrhythmias.Richard Tang, Saurabh Vyas.[pdf]Predicting Kidney Cancer Survival From Genomic Data.Rishi Bedi, Duc Nguyen, Christopher Sauer, Benedikt Buenz.[pdf]Multiclass Sentiment Analysis of Movie Reviews.Robert Chan, Michael Wang.[pdf]Classification and Regression Approaches to Predicting US Senate Elections.Rohan Sampath, Yue Teng.[pdf]Learning from Quantified Self Data.Roshan Vidyashankar.[pdf]Predict Influencers in the Social Network.Ruishan Liu, Yang Zhao, Liuyu Zhou.[pdf]Bias Detector.Rush Moody.[pdf]Constructing Personal Networks Through Communication History.Ryan Houlihan, Hayk Matirosyan.[pdf]Modeling Protein Interactions Using Bayesian Networks.Sabeek Pradhan, Shayne Longpre, Varun Vijay.[pdf]Topic Analysis of the FCC’s Public Comments on Net Neutrality.Sachin Padmanabhan, Leon Yao, Luda Zhao, Timothy Lee.[pdf]Predicting Hospital Readmissions.Sajid Zaidi.[pdf]Analyzing Positional Play in Chess Using Machine Learning.Sameep Bagadia, Pranav Jindal, Rohit Mundra.[pdf]Yelp Restaurants’ Open Hours.Samuel Bakouch, Adrien Boch, Benjamin Favreau.[pdf]Identifying Arrhythmia from Electrocardiogram Data.Samuel McCandlish, Taylor Barrella.[pdf]Diagnosing and Segmenting Brain Tumors and Phenotypes using MRI Scans.Samuel Teicher, Alexander Martinez.[pdf]Exploring the Genetic Basis of Congenital Heart Defects.Sanjay Siddhanti, Jordan Hannel, Vineeth Gangaram.[pdf]Attribution of Contested and Anonymous Ancient Greek Works.Sarah Beller, James Spicer.[pdf]Object Detection for Semantic SLAM using Convolutional Neural Networks.Saumitro Dasgupta.[pdf]Sentiment as a Predictor of Wikipedia Editor Activity.Sergio Martinez-Ortuno, Deepak Menghani, Lars Roemheld.[pdf]Blowing Up The Twittersphere- Predicting the Optimal Time to Tweet.Seth Hildick-Smith, Zach Ellison.[pdf]Evergreen Classification_ Exploring New Features.Shailesh Bavadekar.[pdf]Detecting Lane Departures Using Weak Visual Features.Shane Soh, Ella Kim.[pdf]Re-clustering of Constellations through Machine Learning.Shanshan Xu, Kaifeng Chen, Yao Zhou.[pdf]Application of Neural Network In Handwriting Recognition.Shaohan Xu, Qi Wu, Siyuan Zhang.[pdf]Recognition and Classification of Fast Food Images.Shaoyu Lu, Sina Lin, Beibei Wang.[pdf]Reduced Order Greenhouse Gas Flaring Estimation.Sharad Bharadwaj, Sumit Mitra.[pdf]Blood Pressure Detection from PPG.Sharath Ananth.[pdf]Predicting Low Voltage Events on Rural Micro-Grids in Tanzania.Shea Hughes, Samuel Steyer, Natasha Whitney.[pdf]Amazon Employee Access Control System_Updated_Version.Shijian Tang, Jiang Han, Yue Zhang.[pdf]Prediction Onset Epileptic.Shima Alizadeh, Scott Davidson, Ari Frankel.[pdf]Evaluating Pinch Quality of Underactuated Robotic Hands.Shiquan Wang, Hao Jiang.[pdf]Reinforcement Learning With Deeping Learning in Pacman.Shuhui Qu, Tian Tan,Zhihao Zheng.[pdf]Language identification and accent variation detection in spoken language recordings.Shyamal Buch, Jon Gauthier, Arthur Tsang.[pdf]Enhancing Cortana User Experience Using Machine Learning.Siamak Shakeri, Emad Elwany.[pdf]Who Matters.Sid Basu, David Daniels, Anthony Vashevko.[pdf]Predicting Heart Attacks.Sihang Yu, Yue Zhao, Xuyang Zheng.[pdf]Predicting Seizures in Intracranial EEG Recordings.Sining Ma, Jiawei Zhu.[pdf]Structural Health Monitoring in Extreme Events from Machine Learning Perspective.Sophia Zhou,Jingxuan Zhang.[pdf]On-line Kernel Learning for Active Sensor Networks.Stefan Jorgensen.[pdf]ECommerce Sales Prediction Using Listing Keywords.Stephanie Chen.[pdf]Review Scheduling for Maximum Long-Term Retention of Knowledge.Stephen Barnes, Cooper Frye, Khalil Griffin.[pdf]Adaptive Spaced Repetition.Stephen Koo, Sheila Ramaswamy.[pdf]Do a Barrel Roll.Steven Ingram, Tatiana Kuzovleva.[pdf]Oil Field Production using Machine Learning.Sumeet Trehan.[pdf]Predicting Success for Musical Artists through Network and Quantitative Data.Suzanne Stathatos, Zachary Yellin-Flaherty.[pdf]Better Models for Prediction of Bond Prices.Swetava Ganguli, Jared Dunnmon.[pdf]Classifying the Brain 27s Motor Activity via Deep Learning.Tania Morimoto,Sean Sketch.[pdf]Prediction of Bike Rentals.Tanner Gilligan, Jean Kono.[pdf]Classification of Alzheimer’s Disease Based on White Matter Attributes.Tanya Glozman, Rosemary Le.[pdf]MoralMachines- Developing a Crowdsourced Moral Framework for Autonomous Vehicle Decisions.Tara Balakrishnan, Jenny Chen, Tulsee Doshi.[pdf]Context Specific Sequence Preference Of DNA Binding Proteins.Tara Friedrich.[pdf]Predicting Reddit Post Popularity ViaInitial Commentary.Terentiev Tempest.[pdf]Machine Learning for Continuous Human Action Recognition.Tian Tang.[pdf]Predicting Pace Based on Previous Training Runs.Tiffany Jin.[pdf]Probabilistic Driving Models and Lane Change Prediction.Tim Wheeler.[pdf]Multiple Sensor Indoor Mapping Using a Mobile Robot.Timothy Lee.[pdf]Bone Segmentation MRI Scans.Todor Markov William McCloskey.[pdf]#Rechorder Anticipating Music Motifs In Real Time.Tommy Li, Yash Savani, Wilbur Yang.[pdf]Prediction and Classification of Cardiac Arrhythmia.Vasu Gupta, Sharan Srinivasan, Sneha Kudli.[pdf]Predicting DJIA Movements from the Fluctuation of a Subset of Stocks.Veronique Moore.[pdf]Sentiment Analysis for Hotel Reviews.Vikram Elango, Govindrajan Narayanan.[pdf]Mood Detection with Tweets.Wen Zhang, Geng Zhao, Chenye Zhu.[pdf]Comparison of Machine Learning Techniques for Magnetic Resonance Image Analysis.Wendy Ni, Xinwei Shi, Umit Yoruk.[pdf]Object Recognition in Images.Wenqing Yang, Harvey Han.[pdf]3D Scene Retrieval from Text.Will Monroe.[pdf]Predicting Breast Cancer Survival Using Treatment and Patient Factors.William Chen, Henry Wang.[pdf]Parking Occupancy Prediction and Pattern Analysis.Xiao Chen.[pdf]Supervised DeepLearning For MultiClass Image Classification.Xiaodong Zhou.[pdf]User Behaviors Across Domains .Xiaofei Fu, Norman Yu, Abhishek Garg.[pdf]Seizure forecasting.Xiaoying Pang.[pdf]Stock Trend Prediction with Technical Indicators using SVM.Xinjie Di.[pdf]Predicting Usefulness of Yelp Reviews.Xinyue Liu, Michel Schoemaker, Nan Zhang.[pdf]Obstacles Avoidance with Machine Learning Control Methods in Flappy Birds Setting.Yi Shu, Ludong Sun, Miao Yan, Zhijie Zhu.[pdf]Yelp User Rating Prediction.Yifei Feng, Zhengli Sun.[pdf]Demand Prediction of Bicycle Sharing Systems.Yu-chun Yin, Chi-Shuen Lee, Yu-Po Wong.[pdf]Facial Keypoints Detection.Yue Wang,Yang Song.[pdf]Is Beauty Really In The Eye Of The Beholder.Yun (Albee) Ling, Jocelyn Neff, and Jessica Torres.[pdf]Sentiment Analysis of Yelp’s Ratings Based on Text Reviews.Yun Xu, Xinhui Wu, Qinxia Wang.[pdf]Multiclass Classifier Building with Amazon Data to Classify Customer Reviews into Product Categories.Yunzhen Hu, Te Hu, Haier Liu.[pdf]An Energy Efficient Seizure Prediction Algorithm.Zhongnan Fang, Yuan Yuan, Andrew Weitz.[pdf]Classifier Comparisons On Credit Approval Prediction.Zhoutong Fu, Zhedi Liu.[pdf]Appliance Based Model for Energy Consumption Segmentation.Zi Yin, Thanchanok Teeraratkul, Nutthavuth Tamang.[pdf]analysis on 1s1r array.Zizhen Jiang.[pdf]Video Series:https://www.youtube.com/watch?v=p4FR37aJSKchttps://www.youtube.com/watch?v=5B80x26K8cQhttps://www.youtube.com/watch?v=86lUBfVMe24https://www.youtube.com/watch?v=Yceqk8vmXPMhttps://www.youtube.com/watch?v=BBwEF6WBUQshttps://www.youtube.com/watch?v=fbAdS063bk4https://www.youtube.com/watch?v=svz28L6Ay_chttps://www.youtube.com/watch?v=Ns4aJ-DfoKYhttps://www.youtube.com/watch?v=HF6um7Txmh4https://www.youtube.com/watch?v=eJd3PUhj3Nshttps://www.youtube.com/watch?v=j11fYpycAhkhttps://www.youtube.com/watch?v=LdNYz5YTLhUhttps://www.youtube.com/watch?v=5TkX1mX7elEhttps://www.youtube.com/watch?v=ZX2Hyu5WoFghttps://www.youtube.com/watch?v=cTrG81H08Bkhttps://www.youtube.com/watch?v=vOEushDQyj0https://www.youtube.com/watch?v=qrHhO9E4lIshttps://www.youtube.com/watch?v=G8_PUk50qpchttps://www.youtube.com/watch?v=_X7HfmN63r4https://www.youtube.com/watch?v=N3BJDnDNuVUhttps://www.youtube.com/watch?v=4e3NvB0nc2Mhttps://www.youtube.com/watch?v=lTPO8rrzracFurther 35 Project Ideas or Suggestions which might interest you.1. AI (Artifical Intelligence) Based Image Capturing and transferring to PC/CCTV using Robot2. Material Dimensions Analyzing Robot3. An intelligent mobile robot navigation technique using RFID Technology4. IVRS Based Robot Control with Response & Feed Back5. Library Robot – Path Guiding Robotic System with Artificial Intelligence using Microcontroller6. Wireless Artificial Intelligence Based Fire Fighting Robot for Relief Operations7. A Humanoid Robot to Prevent Children Accidents8. Motion Detection, Robotics Guidance & Proximity Sensing using Ultrasonic Technology9. Robust Sensor-Based Navigation for Mobile Robots10. Visual tracking control to fast moving target for stereo vision robot11. A Voice Guiding System for Autonomous Robots12. Artificial Intelligent based Solar Vehicle13. Mobile robot control based on information of the scanning laser range sensor14. Walking Robot with Infrared Sensors / Light Sensors / RF Sensor / Tactile Sensors15. IVRS Based Control of Three Axis Robot With Voice Feed back16. Intelligent Mobile Robot for Multi Specialty Operations17. Sensor Operated Path Finding Robot (Way Searching)18. Design and Development of Obstacle Sensing and Object Guiding Robot19. SMS controlled intelligent searching and pick and place moving robot20. Artificial Intelligence Based Image Capturing and Transferring to PC using Robot21. Artificial Intelligent Based Remote controlled Automatic Path finding Cum Video Analyzing Robot22. Wall Follower Robot with The Help of Multiple Artificial Eyes23. Sensor Operated Automatic Punching robot24. Fire Fighting Robotics with AI (Artificial Intelligence) and WAP25. Intelligent Robot with Artificial Intelligence computer Brain system26. Remote controlled Pneumatic Four Axis Material Handling Robot27. Advanced Robotic Pick and Place Arm and Hand System28. Voice Controlled Material handling Robot29. A Hands Gesture Control System of for an Intelligent Robot30. Robotic Vision and Color Identification System with Solenoid Arm for Colored Material Separation31. Artificial Intelligence Based Fire fighting AGV32. SMS controlled video analyzing robot33. Staircase Climbing Robot – Implemented in Multi-Domain Approach34. Fully Automated Track Guided Vehicle (ATGV) Robot35. PC based wireless Pick and Place jumping robot with remote control36. Three Axis Robotics With Artificial Intelligence (AI)

I recently wrote a comprehensive guide about exactly the same thing (link here)Build a solid career in tech without a CS majorAlice is a 2nd year material science and metallurgical engineering student at IIT Bombay. She worked hard during her JEE preparation, but ended up screwing JEE. She secured a rank around 2,000. She is from a middle class family and she wanted to opt for Computer Science so that she can build a career in tech and support her family and make her parents proud. However, during JEE counseling, she was able to narrow down her choices to the following:Choose CS at a tier 2 collegeChoose IIT Bombay material science and metallurgical engineeringSince she had heard a lot about IIT Bombay, she ended up choosing IIT Bombay material sciences. However, soon after a few courses in the first year, she realized that she doesn’t like her stream and rather wants to build a career in tech. She also realizes that it is impossible to get her branch changed to Computer Science because the competition is too stiff and her meagre 7 pointer is way below the cutoff of 9.6.Now she is stuck with:Low gradesA branch that she doesn’t likeCannot pursue her love for programmingWorried about jobs and placements at the end of undergradAre you also someone who is like Alice? Did you also choose a branch just for the sake of getting a better college? Are you from a middle class family and want to use your undergrad to build a solid career in tech so that you can support your family? Are you the one who has lost all hope of your career in tech after your first year of undergrad?If the answer to these questions is ‘yes’, I have a surprise for you. Read on!Let me talk a bit about myself. I am a fourth year Computer Science and Engineering undergrad at IIT Bombay. I have spent 3.5 excellent years at IIT Bombay and I have 3 more months before I graduate. This place is excellent, full of smart people. This place has given me a lot — I was a student, this place made me an engineer. I feel like I owe a lot to my college.I have always seen people complain about their branch. This is what I hear quite often from my friends in other branches:I always wanted to study Computer Science, but ah, only top 50 rankers get it, I wasn’t even top 500.My branch is extremely boring. Most of it is cramming. It sucks!I wish I could go back and choose Computer Science in that tier 2 college. Why the hell did I choose my branch?There was a common behavior among all of these people — they all wanted to study CS, but could not do so. JEE rank is the culprit. What was more surprising was that most of them did not utilize the gazillions of programming resources available on the internet that claim to make you a programmer.Then I had a word with a few of them and I got to know that they are confused. Below are the most common questions:How should I proceed ahead?Should I learn web development?Should I try Android app development?What programming language should I learn?How many programming languages should I learn?How to make a website?Should I try freelancing?I was in close contact with a friend of mine who was in a situation very similar to Alice. Let us call my friend as Bob. Bob was fed up of his branch. His only aim was to go in the industry and earn money and make his parents proud. Since I was from Computer Science background, I tried helping Bob and within 2 years, this is what Bob’s boasts off:Hired as a software engineer at a decent tech company with twice the average package of an IITian. No doubt, Bob grabbed the highest package in his department where all other people were below the average packageSoftware engineering internship at a Mumbai based startup at the end of his third yearToday, Bob is happy and is looking forward to his life ahead as a successful software engineer. He is happy that he will earn enough to support his family and himself.Plenty of resources on the internet claim to teach you programming, but the fact is that none of them give a proper road-map and non-CS students find it really hard to figure out what should be done first and what should be done later. They end up picking a difficult topic and then give up easily. For instance, Bob wanted to try android app development in his 2nd year but gave up because he couldn’t understand even the basics.In this blog post, I want to target people like Alice and Bob and want to create a resource that will help every non-CS student build a career as a software engineer. My vision in writing this blog post is that every student has a right to learn Computer programming in the right way. Every student should have enough resources that can help her/him to build a career as a software engineer.Enough of context, let us begin :)I am assuming that you are probably in your 2nd/3rd/4th year of undergrad in a non-CS department, looking for building a career as a software engineer. I further assume that you have done a basic programming course, which is typically compulsory in most colleges. This means that you are aware of at least one of these programming languages — C, C++, Java, Python.First a bit of motivation:The demand for software engineers in India is very high and with more and more new startups, the demand will certainly increase.The starting salaries of software engineers in India are typically twice the salary of other streams. If you are from a tier 1 college, expect even more.Some famous person has said — the best investment you can do to yourself in today’s era is to teach yourself how to program.Let us now talk about how exactly your approach should be so as to achieve your goal of becoming a software engineer.3rd semesterBy the end of first year, you would have certainly completed a basic programming course. For your 3rd semester, you should aim for a course in probability and statistics. Almost all colleges offer such courses and you should enroll in the course offered by your institute. You can choose to sit through the course. But definitely take a probability class early in your curriculum. I have heard that the course offered by MIT OCW is quite good.Taking probability class will also help you reinforce some of your linear algebra concepts which are important for many CS courses.4th semesterTake the following 2 courses:Data structures and algorithmsDiscrete mathematicsData structures and algorithms is a course without which you cannot proceed ahead in computer science. It is a fundamental course and every student must take one such course.This course will be slightly hard. It is highly technical and even the best students get bowled when challenging data structures and algorithms problems are thrown. This course will literally be a test of your patience and so, be patient. If you are able to complete this course, you will be 50% closer to your goal.Discrete mathematics is a course that teaches you mathematics for computer science. You will be studying mathematical induction, combinatorics and other stuff.Here are the resources I would strongly recommend:Algorithms, Part I — Princeton University | Coursera. This is an excellent course. The course is taught in Java. If you don’t know Java, that’s okay. Spend considerable time in understanding what the professor is teaching and try to implement it in whichever programming language you know.Mathematics for Computer Science. This course is offered by MIT and known to be quite good.Recommended books:For data structures and algorithms, I would recommend the book suggested by Robert Sedgewick. The other recommended book is Cormen, but it is slightly more involved and contains rigorous mathematics which you might not appreciate.For discrete mathematics, I would recommend Kenneth Rosen — an excellent book.Keep in mind — write as much code as you can. Unless you write code, you won’t learn. Try to implement everything you learn in Data structures class.Summer break after 2nd yearUse the summer break to hone your programming skills. Head to this link — Sphere Online Judge (SPOJ). SPOJ is an online judge. What is that?SPOJ is an archive of problems that are to be solved by writing code. Consider this simple problem — SPOJ.com — Problem TEST. You need to take input from the user until the user enters ‘42’. Stop as soon as you get 42. Now, observe how to solve this here — Solution to TEST in C. Basically, programming judges have very strict submission guidelines. Don’t print “Enter a number:” when you want to take a number as input. It doesn’t work that way. You submit the code without printing crap. Just print what is specified in the problem statement. Read the sample test cases to get an idea. Do a Google search to understand how online judges work.Solve the first 100 problems in the link that I gave you above. Trust me, you will become a coding ninja if you do this. You will be better than some of your CS friends at programming. No, I am not lying :)100 problems isn’t a big goal. Try solving 2–3 per day and you should be done in 1–1.5 months depending on your speed.Spend time here. If you are unable to get a solution, try harder. Read comments to get hints. Use Google search to get hints. After trying for some 30 or so minutes, if you don’t get a solution, try searching for solution on Google — ‘SPOJ X solution’ where X is the problem code.Your goal should be to learn how to write code, learn the implementations of common algorithms, learn the usage of STL.After you have solved first 5–10 problems on SPOJ, I would also recommend taking a look at this Getting Started with the Sport of Programming. This doc will help you understand things better.5th semesterDuring 5th and 6th semester, you should start searching for internships which you can take up at the end of your third year.However, that will be a side task. Primary task during the 5th semester should be to:Learn web developmentLearn android app developmentYou should get at least 3 projects on your resume at the end of 5th semester:2 web development projects1 android app development projectOur first task would be to learn Django.What is it? It is a Python based web development framework.Why learn it? Django is in high demand among Indian startups these days. Also, it is easy to learn.How do I learn it? Head straight to this link — Django Girls Tutorial. Don’t be sad at the name if you are a boy. Nothing sexist here :) This is one of the best Django tutorials out there. Spend a week’s time understanding it. Spend time in understanding how Django works — model, view, controller architecture. If you follow this tutorial religiously, you have achieved 3 things:You now understand basics of Web development in DjangoYou just picked up basics of PythonYou have a decent project to write on your resumeOnce you are done with the Django girls tutorial, the next thing you should try is to build your own Django app. I have a few suggestions for you:Build a photo gallery app — take a hash tag from the user and use TwitterAPI to gather images of that hash tag in a photo gallery. This might be helpful: amangoeliitb/Photo-Gallery-Web-ApplicationA simple banking application — try making both a customer and an employee account.A student dashboard that shows the performance of student.Oh ya, I forgot to tell — make a Github account. Github is a ‘social network’ for programmers. People upload their source codes on Github. There is also something called as ‘git’, which is a version management system. Take this short course on git — How to Use Version Control in Git & GitHub | Udacity. By the way, git is worth learning because you can put it on your resume!There is another important thing I forgot to tell you about — stackoverflow. As a programmer you are bound to face errors and exceptions. What to do? There is an extremely simple technique to deal with errors. Copy the damn error, paste it in your search bar and hit enter. Viola! Open the first 3 links you get on Google search. With a high probability, someone has already faced the error you got and has written a solution on stackoverflow. Stackoverflow links are generally reliable and you can expect them to give you the right answer. Be patient. Read and try. Your code might break. But that’s okay. Use undo. But don’t be afraid of breaking things else you won’t learn.Cool, so now you know web development, Python and you have 2 awesome projects on your resume. Let us move to Android app development. Here are the steps to follow:Head to this link: Android | Udacity. Udacity is a platform in which big tech companies offer courses that you can take up to learn various skills in software engineering. Google has built some excellent Android courses on Udacity and you should definitely take a look at them. Start from beginner level courses. They are very simple and might get completed in a day or two. You should spend at least 1–2 hours a day in these courses. Once you are done with beginner level courses, take up intermediate level courses. Of course, do the free ones. There is no need to spend money on any course/nanodegree. Learning programming should be free for everyone :)Android might be slightly frustrating. The Java used in Android is slightly different from the usual Java in the sense that it is advanced and has a lot of library functions. Don’t get bogged down by it. Remember, you need to be a software engineer. We software engineers are known to solve problems ;) As again, I would suggest that you should use Google search heavily for any errors. Be patient because Android is slightly hard.At the end, you would have 3 more things on your resume:Android app developmentJavaAn android app based projectWith this much on your resume, you are sure to get an internship.6th semesterIn this semester, you should get serious about your internship (if you haven’t got one yet). Anyway, here are the pointers for internship:AngelList is an excellent platform where startups are looking for interns. Make an AngelList account and add your projects and skills on it. You are sure to gather attention of some startups with those awesome Android and web development skills.Search for other internship portals. Be active on LinkedIn.Start preparing for interviews. The way hiring in computer science works is that you are shortlisted for interviews based on your resume. During interviews, you are asked data structures and algorithms based problems. The level of problems would be similar to what you have been doing on SPOJ so you can be happy that your hard work will finally pay off. I would recommend continuing SPOJ practice. It is easier to lose skills than pick up skills.To prepare for interviews, use the following 3 excellent sources:Cracking the coding Interview — this book is the bible for programming interviews. Purchase it or download a pdf (piracy is bad). Try reading the theory and solve the problems. Try to actually implement the solutions.Coding Interview Questions — This is a brilliant platform to hone your interview skills.GeeksforGeeks — this is an great programming blog/archive.Also, I would suggest that you should be prepared with questions from your 5th semester projects. You should be able to explain the code you wrote. Interviewer might ask you about a specific library you used. Don’t worry, you should have a high level idea that you should be able to explain. No one will ask you syntax.That was about internships. Besides the internship, you should try taking up some miscellaneous courses like:Machine Learning — Machine Learning — Stanford University | CourseraIntro to Machine Learning Course | UdacityCryptography — Applied Cryptography and Encryption Class Online | UdacityThese courses should help you put 2 more projects on your resume and also expand your CS knowledge. No doubt they will also open up more internship domains for you:Data/ML engineer internSecurity engineer internSummers at the end of 3rd yearEnjoy your internship. Work hard and try to get a return offer7th semesterPrepare hard for placements during this sem. The following topics are asked during placements:Data structures and algorithms — the standard bread and butter of CSProbability — school level prob/stats questions. These should be easy for youDatabases and Operating systems — we are yet to talk about thisSince you are not from CS department, a lot of companies won’t be open for you during placements. But don’t worry. Quite a few companies would be willing to take you if you have worked hard over the past 2 years. Aim specifically for web/android dev positions. These are easy to grab.Now let us talk about databases and operating systems (OS):Databases — in your Django web app, you would have used SQLite/MySQL/Postgres as your database. A database is a special kind of data structure that stores data in hard disk. Some companies like to ask databases related questions to the candidates. Being a non CS student, of course you aren’t expected to do a formal databases course (if you can, then that’s a big plus though!). Search for databases interview questions to get a basic idea of what is asked. I guess I will leave this point open ended because by this time, you would have become smart enough to figure this out yourself :)Operating systems — pretty much the same applies here as well. Doing a quick Google search for operating systems interview questions will give you enough practice problems which will be fine for most interviews.If you are interested, you should take up online courses on databases and OS:Stanford databasesIntro to Relational Databases | UdacityIntroduction to Operating Systems | UdacityHaving said that, keep in mind that data structures and algorithms are something very important for placements and InterviewBit should be the one place where you should spend your maximum time.If you have followed the above points seriously and worked hard for the 2.5 years, trust me, your hard work will pay off now. You are sure to bag a decent package during the placements. Bob was placed right on day 3. He was the only one in his department who got placed in the first week. And his package was twice the average package of an IITian.8th semesterDuring this semester, you have multiple options:If you got a job, you can chill out.If you haven’t got a job yet (very unlikely), you should consider applying to startups on AngelList. The startups on AngelList are actively looking for full time hires.Take up more projects — you can continue take up courses and continue working on various projects. Here is a brilliant resource for you — Students — Guide to Technical Development — Google CareersIntern remotely at a startup — again, AngelList comes to the rescue. You can keep the course load lesser and rather do a remote internship at a startup. This will not only give you experience, but also if you work hard, you might end up with another job offer.I guess I wrote a lot and I will be concluding now. In the end, I would like to add a few basic pointers specific to CS:CS is easy provided you understand that you need to implement stuff (write actual code) otherwise you won’t be able to learn things.Don’t be afraid to try out new things. Don’t think that — oh this is too hard, and is meant for experts. No. Nothing is meant for experts. All it takes is those 5–10 minutes of sincere reading and I can guarantee that there is nothing you cannot pickup.Don’t be afraid of breaking things. Don’t think that — oh my machine might break if I do that. At the very most, you might end up with a broken software, which can be easily fixed. It is unlikely that you will do a damage to hardware.Learn with friends. You will be amazed to see how smart the people around you are and you can learn a lot by interacting with others.I forgot to add a great resource that I came to know about recently: www.hackr.io. It is a great platform to find tutorials for various topics on the internet.We at CareerHigh are building something called as Non-CS Academy — a platform for non-CS students and working professionals to learn right skills so as to shift to the Computer Science domain. You can visit it here: https://careerhigh.in/non-cs-academy/.Good luck and all the very best for your future and career!

Below is the List of Distinguished Final Year 100+ Machine Learning Projects Ideas or suggestions for Final Year students you can complete any of them or expand them into longer projects if you enjoy them.Nonlinear Reconstruction of Genetic Networks Implicated in AML.Aaron Goebel, Mihir Mongia .[pdf]Can Machines Learn Genres.Aaron Kravitz, Eliza Lupone, Ryan Diaz.[pdf]Identifying Gender From Facial Features.Abhimanyu Bannerjee, Asha Chigurupati.[pdf]Equation to LaTeX.Abhinav Rastogi, Sevy Harris.[pdf]Intensity prediction using DYFI.Abhineet Gupta.[pdf]Artificial Intelligence on the Final Frontier – Using Machine Learning to Find New Earths.Abraham Botros.[pdf]Life Expectancy Post Thoracic Surgery.Adam Abdulhamid, Ivaylo Bahtchevanov, Peng Jia.[pdf]Making Sense of the Mayhem- Machine Learning and March Madness.Adam Ginzberg, Alex Tran.[pdf]Better Reading Levels through Machine Learning.AdamGall.[pdf]What are People Saying about Net Neutrality.Adison Wongkar, Christoph Wertz.[pdf]Bird Species Identification from an Image.Aditya Bhandari, Ameya Joshi, Rohit Patki.[pdf]Stay Alert.Aditya Sarkar, Quentin Perrot, Julien Kawawa.[pdf]A bigram extension to word vector representation.Adrian Sanborn, Jacek Skryzalin.[pdf]Mining for Confusion – Classifying Affect in MOOC Learners’ Discussion Forum Posts.Akshay Agrawal, Shane Leonard.[pdf]Cardiac Arrhythmias Patients.AlGharbi Fatema, Fazel Azar, Haider Batool.[pdf]Prediction of Average and Perceived Polarity in Online Journalism.Albert Chu, Kensen Shi, Catherine Wong.[pdf]Cardiac Dysrhythmia Detection with GPU-Accelerated Neural Networks.Albert Haque.[pdf]Nicolas Sanchez Ruck Those Stats!.Alejandro Sanchez.[pdf]Classifying Wikipedia People Into Occupations.Aleksandar Gabrovski.[pdf]Classification of Soil Contamination.Aleo Mok.[pdf]Automated Essay Grading.Alex Adamson, Andrew Lamb, Ralph Ma.[pdf]Relative and absolute equity return prediction using supervised learning.Alex Alifimoff, Axel Sly.[pdf]Seizure Prediction from Intracranial EEG Recordings.Alex Fu, Spencer Gibbs, Yuqi Liu.[pdf]Predicting Seizure Onset with Intracranial Electroencephalogram(EEG) Data.Alex Greaves, Arushi Raghuvanshi, Kai-Yuan Neo.[pdf]Classifying Complex Legal Documents.Alex Ratner.[pdf]Machine Learning Applied to the Detection of Retinal Blood Vessels.Alex Yee.[pdf]Survival Outcome Prediction for Cancer Patients.Alexander Herrmann .[pdf]Predicting Cellular Link Failures to Improve User Experience on Smartphones.Alexander Tom, Srini Vasudevan.[pdf]Yelp Personalized Reviews.Alexis Weill, Thomas Palomares, Arnaud Guille.[pdf]KMeansSL.Alfred Xue, Colin Wei.[pdf]Strength in numbers_ Modelling the impact of businesses on each other.Amir Sadeghian, Hakan Inan, Andres Noetzli.[pdf]Correlation Based Multi-Label Classification.Amit Garg, Jonathan Noyola, Romil Verma.[pdf]Landmark Recognition Using Machine Learning.Andrew Crudge, Will Thomas, Kaiyuan Zhu.[pdf]CarveML an application of machine learning to file fragment classification.Andrew Duffy.[pdf]rClassifier.Andrew Giel,Jon NeCamp,HussainKader.[pdf]Using Vector Representations to Augment Sentiment Analysis Training Data.Andrew McLeod, Lucas Peeters.[pdf]What Project Should I Choose.Andrew Poon.[pdf]Analyzing Vocal Patterns to Determine Emotion.Andy Sun, Maisy Wieman.[pdf]Predicting the Commercial Success of Songs Based on Lyrics and Other Metrics.Angela Xue, Nick Dupoux.[pdf]Application Of Machine Learning To Aircraft Conceptual Design.Anil Variyar.[pdf]Extracting Word Relationships from Unstructured Data.Anirudha Bhat, Krithika Iyer, Rahul Venkatraj.[pdf]Machine Learning for Predicting Delayed Onset Trauma Following Ischemic Stroke.Anthony Ma, Gus Liu.[pdf]Classifying Online User Behavior Using Contextual Data.Anunay Kulshrestha, Akshay Rampuria, Aditya Ramakrishnan.[pdf]Real Time Flight Path Optimization Under Constraints Using Surrogate Flutter Function.Arthur Paul-Dubois-Taine.[pdf]Real-Time Dense Map Matching with Naive Hidden Markov Models Delay versus Accuracy.Arun Jambulapati, Juhana Kangaspunta, Youssef Ahres, Loek Janssen.[pdf]Prediction Function from Sequence in Venom Peptide Families.Arvind Kannan, G. Seshadri.[pdf]Restaurant Recommendation System.Ashish Gandhe.[pdf]Home Electricity Load Forecasting.Atinuke Ademola Idowu, Pawel Kupsc, Sonya Mollinger.[pdf]Learning Dota 2 Team Compositions.Atish Agarwala, Michael Pearce.[pdf]Applying Deep Learning to derive insights about non-coding regions of the genome.Avanti Shrikumar, Anna Saplitski, Sofia Luna Frank-Fischer.[pdf]Classification of Higgs Jets as Decay Products of a Randall-Sundrum Graviton at the ATLAS Experiment.Aviv Cukierman, Zihao Jiang.[pdf]SemenFertilityPrediction.Axel Guyon,Florence Koskas,Yoann Buratti.[pdf]Sentiment Analysis Using Semi-Supervised Recursive Autoencoders and Support Vector Machines.Bahareh Ghiyasian, Yun Fei Guo.[pdf]Classifying Syllables in Imagined Speech using EEG Data.Barak Oshri, Nishith Khandwala, Manu Chopra.[pdf]Abraham Starosta-Typeguess.Baris Akis, Mariano Sorgente.[pdf]Predicting Usefulness of Yelp Reviews.Ben Isaacs, Xavier Mignot, Maxwell Siegelman.[pdf]Predicting Soccer Results in the English Premier League.Ben Ulmer, Matt Fernandez.[pdf]Detecting Heart Abnormality using ECG with CART.Ben Zhou, Gaspar Garcia, Paurakh Rajbhandary.[pdf]Down and Dirty with Data.Bharat Arora, Roger Davidson, Christopher Wildman.[pdf]Hierarchical Classification of Amazon Products.Bin Wang, Shaoming Feng.[pdf]Predicting high-risk countries for political instability and conflict.Blair Huffman, Emma Marriott, April Yu.[pdf]Machine Learning Implementation in live-cell tracking.Bo Gu.[pdf]Any Given Sunday.Bobak Moallemi, Matthew Wilson, Steven Hoerning.[pdf]P300 Error Detection.Boyeaux Felix,Chatoor Nehan.[pdf]Automated Canvas Analysis for Painting Conservation.Brendan Tobin.[pdf]Office Appliance Classification.Brock Petersen, Gerrit de Moor, Elissa Goldner.[pdf]Sentiment Analysis on Movie Reviews.Cai Xiao, Ya Wang.[pdf]Predicting Mobile Application Success.Cameron Tuckerman.[pdf]Modeling Activity Recognition Using Physiological Data Collected from Wearable Technology.Cezanne Camacho, Jennifer Li, Jeffrey Yang.[pdf]Neural Network Joint Language Model.Charles Qi.[pdf]Yelp Recommendation System Using Advanced Collaborative Filtering.Chee Hoon Ha.[pdf]Prediction of Yelp Review Star Rating using Sentiment Analysis.Chen Li, Jin Zhang.[pdf]Classification of Bad Accounts in Credit Card Industry.Chengwei Yuan.[pdf]Classification Of Musical Playing Styles.Chet Gnegy.[pdf]Email Filtering By Response Required.Chris Knight.[pdf]Forecasting Utilization in City Bike-Share Program.Christina Lee, David Wang, Adeline Wong.[pdf]Recommender.Christopher Aberger.[pdf]Predicting Cell Type-Specific Chromatin States from Genetic Regulatory Networks.Christopher Probert, Anthony Ho.[pdf]Pose Estimation Based on 3D Models.Chuiwen Ma, Liang Shi.[pdf]Visual Localization and POMDP for Autonomous Indoor Navigation.Chulhee Yun, Sungjoon Choi.[pdf]Contours and Kernels-The Art of Sketching.Dan Guo,Paula Kusumaputri,Amani Peddada.[pdf]Indoor Positioning System Using Wifi Fingerprint.Dan Li, Le Wang, Shiqi Wu.[pdf]Predicting air pollution level in a specific city.Dan Wei.[pdf]Prediction of Transcription Factors that Regulate Common Binding Motifs.Dana Wyman, Emily Alsentzer.[pdf]Multi-class motif discovery in keratinocyte differentiation.Daniel Kim.[pdf]Defensive Unit Performance Analysis.Daniel ONeel, Reed Johnson.[pdf]Diagnosing Malignant versus Benign Breast Tumors via Machine Learning Techniques in High Dimensions.Danielle Maddix.[pdf]Hacking the Hivemind.Daria Lamberson,Leo Martel, Simon Zheng.[pdf]Diagnosing Parkinson’s from Gait.Daryl Chang, Marco Alban-Hidalgo, Kevin Hsu.[pdf]Implementing Machine Learning Algorithms on GPUs for Real-Time Traffic Sign Classification.Dashiell Bodington, Eric Greenstein, Matthew Hu.[pdf]Vignette.David Eng, Andrew Lim, Pavitra Rengarajan.[pdf]Machine Learning In JavaScript.David Frankl.[pdf]Searching for exoplanets in the Kepler public data.David Glass, Xiaofan Jin.[pdf]Model Clustering via Group Lasso.David Hallac.[pdf]Improving Positron Emission Tomography Imaging with Machine Learning.David Hsu.[pdf]Algorithmic Trading of Futures via Machine Learning.David Montague.[pdf]Topic based comments exploration for online articles.Deepak Zambre, Ajey Shah.[pdf]Personal Legal Counselor and Interpreter of the Law via Machine Learning.Derek Yan, Tianyi Wang, Patrick Chase.[pdf]Personalized Web Search.Dhanraj Mavilodan, Kapil Jaisinghani, Radhika Bansal.[pdf]Detecting Ads in a Machine Learning Approach.Di Zhang.[pdf]Predicting Mitochondrial tRNA Modification.Diego Calderon.[pdf]Collaborative Neighborhoods.Diego Represas, David Dindi.[pdf]Estimation of Causal Effects from Observational Study of Job Training Program.Dmitry Arkhangelsky, Rob Donnelly.[pdf]Deep Leraning Architecture for Univariate Time Series Forecasting.Dmitry Vengertsev.[pdf]Solomon.Do Kwon, Gyujin Oh, Ki Suk Jang, Ji Park.[pdf]Automatic detection of nanoparticles in tissue sections.Dor Shaviv, Orly Liba.[pdf]Implementation of Deep Convolutional NeuralNet on a DSP.Elaina Chai.[pdf]Evergreen or Ephemeral – Predicting Webpage Longevity Through Relevancy Features.Elaine Zhou, Lingtong Sun.[pdf]MacMalware.Elizabeth Walkup.[pdf]Extractive Fiction Summarization Using Sentence Significance Scoring Models.Eric Holmdahl, Ashkon Farhangi, Lucio Tan.[pdf]Identifying And Predicting Market Reactions To Information Shocks In Commodity Markets.Eric Liu, Vedant Ahluwalia, Deepyaman Datta, Dongyang Zhang.[pdf]An EM-Derived Approach to Blind HRTF Estimation.Eric Schwenker.[pdf]The Many Dimensions of Net Neutrality.Erin Antono, Deger Turan, Justine Zhang.[pdf]Learning To Predict Dental Caries For Preschool Children.Fangzhou Guo, Huaiyang Zhong, Yuchen Li.[pdf]Information based feature selection.Farzan Farnia, Abbas Kazerouni, Afshin Babveyh.[pdf]Identifying Elephant Vocalizations.Flavia Crisrtina Grey Rodriguez, Sergio Patricio Figueroa Sanz.[pdf]Predicting Protein Fragment Binding.Flynn Wu.[pdf]Bike Share Usage Prediction in London.Ford Rylander, Bo Peng, Jeff Wheeler.[pdf]Localized Explicit Semantic Analysis.Francis Lewis.[pdf]Robo Brain Massive Knowledge Base for Robots.Gabriel Kho, Christina Hung, Hugh Cunningham.[pdf]Understanding Music Genre Similarity.Gabriela Groth.[pdf]Correlated Feature Selection for Single-Cell Phenotyping.Geoff Stanley.[pdf]Activity Recognition in Construction Sites Using 3D Accelerometer and Gyrometer.Gustavo Cezar .[pdf]Event-based stock market prediction.Hadi Pouransari, Hamid Chalabi.[pdf]Recommendation Based On User Experience.Hai Vu.[pdf]Spectrum Adaptation in Multicarrier Interference Channels.Haleema Mehmood.[pdf]Exploring Potential for Machine Learning on Data About K-12 Teacher Professional Development.Hamilton Plattner.[pdf]Player Behavior and Optimal Team Compositions for Online Multiplayer Games.Hao Yi Ong, Sunil Deolalikar, Mark Peng.[pdf]Algorithmic Trading Strategy Based On Massive Data Mining.Haoming Li, Tianlun Li, Zhijun Yang.[pdf]Face Detection And Recognition Of Drawn Characters.Herman Chau.[pdf]Gene Expression Analysis Of HCMV Latent Infection.Hie Hong.[pdf]A New Kalman Filter Method.Hojat Ghorbanidehno, Hee Sun Lee.[pdf]Using Tweets for single stock price prediction.Hongshan Chu, Ye Tian, Hongyuan Yuan.[pdf]Classification of Human Posture and Movement Using Accelerometer Data.Huafei Wang, Jennifer Wu.[pdf]Naïve Bayes Classifier And Profitability of Options Gamma Trading.HyungSup Lim.[pdf]Vector-based Sentiment Analysis of Movie Reviews.Ian Roberts, Lisa Yan.[pdf]A General-Purpose Sentence-Level Nonsense Detector.Ian Tenney.[pdf]Characterizing Genetic Variation in Three Southeast Asian Populations.Ilana Arbisser, Jonathan Kang.[pdf]Machine Learning for the Smart Grid.Iliana Voynichka.[pdf]Predicting Africa Soil Properties.Iretiayo Akinola, Thomas Dowd.[pdf]Automated Bitcoin Trading via Machine Learning Algorithms.Isaac Madan, Shaurya Saluja, Aojia Zhao.[pdf]SkatBot.Ivan Leung, Pedro Milani, Ben-han Sung.[pdf]Tradeshift Text Classification.Jacob Conrad Trinidad, Ian Torres.[pdf]New York City Bike Share.James Kunz, Everett Yip, Gary Miguel.[pdf]Predicting Seizure Onset in Epileptic Patients Using Intercranial EEG Recordings.Janet An, Amy Bearman, Catherine Dong.[pdf]Predicting Foster Care Exit.Jason Huang.[pdf]Yelp Recommendation System.Jason Ting, Swaroop Indra Ramaswamy.[pdf]Predicting National Basketball Association Game Winners.Jasper Lin, Logan Short, Vishnu Sundaresan.[pdf]Predicting Yelp Ratings From Business and User Characteristics.Jeff Han, Justin Kuang, Derek Lim.[pdf]Predicting Popularity of Pornography Videos.Jessie Duan.[pdf]Accurate Campaign Targeting Using Classification Algorithms.Jieming Wei, Sharon Zhang.[pdf]Forecasting Bike Rental Demand.Jimmy Du, Rolland He, Zhivko Zhechev.[pdf]Predicting User Following Behavior On Tencent Weibo.Jinfeng Huang, Hai Huang, Zhaoyang Jin .[pdf]Improving Taxi Revenue With Reinforcement Learning.Jingshu Wang, Benjamin Lampert.[pdf]Learning Facial Expressions From an Image.Jithin Thomas, Bhrugurajsinh Chudasama, Chinmay Duvedi.[pdf]All Your Base Are Belong To Us English Texts Written by Non-Native Speakers.Joanna Kim, Jonathan Hung.[pdf]Identifying Regions High Turbidity.Joe Adelson.[pdf]A Comparison of Classification Methods for Expression Quantitative Trait Loci.Joe Davis.[pdf]Predicting Mobile Users Future Location.John Doherty .[pdf]Machine Learning Madness.John Gold, Elliot Chanen.[pdf]Semi-Supervised Learning For Sentiment Analysis.John Miller, Aran Nayebi, Amr Mohamed.[pdf]Legal Issue Spotting.John Phillips.[pdf]A novel way to Soccer Match Prediction.Jongho Shin, Robert Gasparyan.[pdf]Morphological Galaxy Classification.Jordan Duprey, James Kolano.[pdf]Predicting Helpfulness Ratings of Amazon Product Reviews.Jordan Rodak, Minna Xiao, Steven Longoria.[pdf]Predicting Course Completions For Online Courses.Joseph Paetz.[pdf]An Adaptive System For Standardized Test Preparation.Julia Enthoven.[pdf]Single Molecule Biophysics Machine Learning For Automated Data Processing.Junhong Choi, Soomin Cho.[pdf]Understanding Comments Submitted to FCC on Net Neutrality.Junhui Mao, Jing Xia, Woncheol Jeong.[pdf]Direct Data-Driven Methods for Decision Making under Uncertainty.Junjie Qin.[pdf]From Food To Wine.Justin Meier.[pdf]Classifying Legal Questions into Topic Areas Using Machine Learning.Karthik Jagadeesh, Brian Lao.[pdf]Predicting Hit Songs with MIDI Musical Features.Kedao Wang.[pdf]Machine Learning Methods for Biological Data Curation.Kelley Paskov.[pdf]Classifying Forest Cover Type using Cartographic Features.Kevin Crain, Graham Davis.[pdf]Peer Lending Risk Predictor.Kevin Tsai,Sivagami Ramiah,Sudhanshu Singh.[pdf]Learning Distributed Representations of Phrases.Konstantin Lopyrev.[pdf]Estimation Of Word Representations Using Recurrent Neural Networks And Its Application In Generating Business Fingerprints.Kuan Fang.[pdf]Gender Identification by Voice.Kunyu Chen.[pdf]Applications Of Machine Learning To Predict Yelp Ratings.Kyle Carbon, Kacyn Fujii, Prasanth Veerina.[pdf]Methodology for Sparse Classification Learning Arrhythmia.Lee Tanenbaum.[pdf]Predicting March Madness.Levi Franklin.[pdf]Net Neutrality Language Analysis.Li Tao, Xinyi Xie.[pdf]Characterizing Atrial Fibrillation Burden for Stroke Prevention.Lichy Han.[pdf]Predict Seizures in Intracranial EEG Recordings.Linyu He, Lingbin Li.[pdf]Automated Music Track Generation.Louis Eugene, Guillaume Rostaing.[pdf]Characterizing Overlapping Galaxies.Luis Alvarez.[pdf]Understanding Player Positions in the NBA.Luke Lefebure.[pdf]Cross-Domain Product Classification with Deep Learning.Luke de Oliveira, Alfredo Lainez, Akua Abu.[pdf]Predicting Heart Attacks.Luyang Chen, Qi Cao, Sihua Li, Xiao Ju.[pdf]Prediction of Bike Sharing Demand for Casual and Registered Users.Mahmood Alhusseini.[pdf]Classification Of Arrhythmia Using ECG Data.Manas Karandikar, Giulia Guidi.[pdf]What Can You Learn From Accelerometer Data.Manikantan Shila.[pdf]Speaker Recognition for Multi-Source Single-Channel Recordings.Maria Frank, Neil Gallagher, Jose Kruse Perin.[pdf]Prediction of consumer credit risk.Marie-Laure Charpignon, Enguerrand Horel, Flora Tixier.[pdf]Machine Learning for Network Intrusion Detection.Martina Troesch, Ian Walsh.[pdf]Predicting Paper Counts in the Biological Sciences.Matt Denton, Jose Hernandez, Debnil Sur.[pdf]Prediction of Price Increase for MTG Cards.Matt Pawlicki, Joe Polin, Jesse Zhang.[pdf]Twitter Classification into the Amazon Browse Node Hierarchy.Matthew Long, Jiao Yu, Anshul Kundani.[pdf]Determining Mood From Facial Expressions.Matthew Wang, Spencer Yee.[pdf]Visualizing Personalized Cancer Risk Prediction.Maulik Kamdar.[pdf]Predicting the Total Number of Points Scored in NFL Games.Max Flores, Ajay Sohmshetty.[pdf]Short Term Power Forecasting Of Solar PV Systems Using Machine Learning Techniques.Mayukh Samanta,Bharath Srikanth,Jayesh Yerrapragada.[pdf]Star-Galaxy Separation in the Era of Precision Cosmology.Michael Baumer, Noah Kurinsky, Max 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fielda.Philip Brodrick, Jacob Englander.[pdf]Anomaly Detection in Bitcoin Network Using Unsupervised Learning Methods.Phillip Pham,Steven Li.[pdf]Two-step Semi-supervised Approach for Music Structural Classificiation.Prateek Verma, Yang-Kai Lin, Li-Fan Yu.[pdf]Domain specific sentiment analysis using cross-domain data.Praveen Rokkam, Marcello Hasegawa.[pdf]Instrumental Solo Generator.Prithvi Ramakrishnan, Aditya Dev Gupta.[pdf]Cross-Domain Text Understanding in Online SocialData.Qian Lin, Shenxiu Liu, Zhao Yang.[pdf]From Paragraphs to Vectors and Back Again.Qingping He.[pdf]HandwritingRecognition.Quan Nguyen, Maximillian Wang, Le Cheng Fan.[pdf]Chemical Identification with Chemical Sensor Arrays.Quintin Stedman.[pdf]Genre Classification Using Graph Representations of Music.Rachel Mellon, Dan Spaeth, Eric Theis.[pdf]Collaborative Filtering Recommender Systems.Rahul Makhijani, Saleh Samaneh, Megh Mehta.[pdf]Detecting The Direction Of Sound With A Compact Microphone 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Series:https://www.youtube.com/watch?v=p4FR37aJSKchttps://www.youtube.com/watch?v=5B80x26K8cQhttps://www.youtube.com/watch?v=86lUBfVMe24https://www.youtube.com/watch?v=Yceqk8vmXPMhttps://www.youtube.com/watch?v=BBwEF6WBUQshttps://www.youtube.com/watch?v=fbAdS063bk4https://www.youtube.com/watch?v=svz28L6Ay_chttps://www.youtube.com/watch?v=Ns4aJ-DfoKYhttps://www.youtube.com/watch?v=HF6um7Txmh4https://www.youtube.com/watch?v=eJd3PUhj3Nshttps://www.youtube.com/watch?v=j11fYpycAhkhttps://www.youtube.com/watch?v=LdNYz5YTLhUhttps://www.youtube.com/watch?v=5TkX1mX7elEhttps://www.youtube.com/watch?v=ZX2Hyu5WoFghttps://www.youtube.com/watch?v=cTrG81H08Bkhttps://www.youtube.com/watch?v=vOEushDQyj0https://www.youtube.com/watch?v=qrHhO9E4lIshttps://www.youtube.com/watch?v=G8_PUk50qpchttps://www.youtube.com/watch?v=_X7HfmN63r4https://www.youtube.com/watch?v=N3BJDnDNuVUhttps://www.youtube.com/watch?v=4e3NvB0nc2Mhttps://www.youtube.com/watch?v=lTPO8rrzracFurther 35 Project Ideas or Suggestions which might interest you.1. AI (Artifical Intelligence) Based Image Capturing and transferring to PC/CCTV using Robot2. Material Dimensions Analyzing Robot3. An intelligent mobile robot navigation technique using RFID Technology4. IVRS Based Robot Control with Response & Feed Back5. Library Robot – Path Guiding Robotic System with Artificial Intelligence using Microcontroller6. Wireless Artificial Intelligence Based Fire Fighting Robot for Relief Operations7. A Humanoid Robot to Prevent Children Accidents8. Motion Detection, Robotics Guidance & Proximity Sensing using Ultrasonic Technology9. Robust Sensor-Based Navigation for Mobile Robots10. Visual tracking control to fast moving target for stereo vision robot11. A Voice Guiding System for Autonomous Robots12. Artificial Intelligent based Solar Vehicle13. Mobile robot control based on information of the scanning laser range sensor14. Walking Robot with Infrared Sensors / Light Sensors / RF Sensor / Tactile Sensors15. IVRS Based Control of Three Axis Robot With Voice Feed back16. Intelligent Mobile Robot for Multi Specialty Operations17. Sensor Operated Path Finding Robot (Way Searching)18. Design and Development of Obstacle Sensing and Object Guiding Robot19. SMS controlled intelligent searching and pick and place moving robot20. Artificial Intelligence Based Image Capturing and Transferring to PC using Robot21. Artificial Intelligent Based Remote controlled Automatic Path finding Cum Video Analyzing Robot22. Wall Follower Robot with The Help of Multiple Artificial Eyes23. Sensor Operated Automatic Punching robot24. Fire Fighting Robotics with AI (Artificial Intelligence) and WAP25. Intelligent Robot with Artificial Intelligence computer Brain system26. Remote controlled Pneumatic Four Axis Material Handling Robot27. Advanced Robotic Pick and Place Arm and Hand System28. Voice Controlled Material handling Robot29. A Hands Gesture Control System of for an Intelligent Robot30. Robotic Vision and Color Identification System with Solenoid Arm for Colored Material Separation31. Artificial Intelligence Based Fire fighting AGV32. SMS controlled video analyzing robot33. Staircase Climbing Robot – Implemented in Multi-Domain Approach34. Fully Automated Track Guided Vehicle (ATGV) Robot35. PC based wireless Pick and Place jumping robot with remote control36. Three Axis Robotics With Artificial Intelligence (AI)