Hippa Privacy Form: Fill & Download for Free

Not unless they’ve put you as a contact on their HIPPA privacy info. form, NO.

The federal form the firearm purchaser must fill out and sign does ask about past mental illness, drug addiction, dishonorable discharge from military service and other relevant issues. However, BATFE doesn’t have access to an individual’s medical history, nor are they qualified to make any medical judgements. HIPPA privacy provisions restrict who may access your medical history and under what circumstances. I feel Big Brother (Orwell, 1984) would gain unhindered access to all medical documents if we ever adopted a single payer national healthcare system. Any mechanism to expand government intrusion into private medical records would have numerous negative consequences.

My gut reaction is: you cannot really sell data science …Let’s try to be more specific - I guess you want to build a business based on data science? Ok, here are your options:you are selling data - not science (that seems to have become a commodity business)you are selling yourself as a data scientist (so some form of consulting I would guess)you are trying to sell under a SaaS model some cute algorithm (say the most top notch classification algorithm on earth)you are selling a ‘solution’ to a somewhat standard data science problem (a cat classification model for facebook picture, sentiment classifier on twitter data)I am sure there are more …Depending on which one you have in mind, what they want to hear is very different. Talking of different: no matter which, you do need to ask yourself why should they listen to YOU?Selling data: do you have a dataset that is a) unique in the sense that nobody else has it (or something like it), b) you are legally (and ethically) allowed to sell it, c) is it valuable (is there a problem for which it would be valuable contrary to say the temperature on the moon by the milli-second), and finally d) (if so far the answers were yes) - can you easily argue/demonstrate its value and uniqueness? The last part is surprisingly hard. Even if it is better/bigger/cleaner/whatever than any available dataset, you will probably have a hard time winning a ‘but mine is bigger than yours’ against an established player with a set of powerpoint slides. One of the most important value proposition is that your data ‘connects’ to other data that somebody already has. Ultimately - you will have to give away a sample so the customer can ‘try’ it out to evaluate the value to the specific problem he or she are trying to solve.Selling yourself: You need a track record and public recognition for it (yep, that means networking, competitions, cases, testimonials, public speaking, etc). So unless you already have a good number of years of experience and people know about you - this is a hard one to start on your own. Better is to join forces with somebody who has and have him a) mentor you and b) help you establish credibility. You also have to have a lot of experience in managing projects (from design to execution). Most data science projects do not fail because of data science/data issues, but because of lack of cooperation with the stakeholders. This is one of the reasons why I do not really believe in the traditional consulting model for data science. In data science you need to iterate a number of times between the task (it often ends up being something different from what you thought initially), the data and the solution before it all ‘fits’ and consulting often does not allow for this.Selling an algorithm: The reality is, algorithms are NOT really differentiators. In fact, in most cases, the ‘best’ performing model is often not being used, besides the fact that good feature construction trumps algorithm almost always. So yeah - maybe you have something that could be 2% better than my trusted logistic regression - but unless you are trying to do trading in financial markets, I do not really care. I want something that is easy to maintain, robust, can be explained easily to whoever needs to understand it. And for most of these requirements - there is so much freeware out there (just look at python these days) that I would not pay a dime for something ‘special’.Selling an solution: Selling a solution is probably your best bet, provided there are not already 10+ solutions for the same thing out there … say entity extraction from documents. Best cases of solutions are where you bring both the algorithm and the data to the table and all the customer needs and gets are the results. Even better if you can easily (not too many men hours) customize the solution to the specific version of the problem (for instance by linking your data to the specific data of the customer). Somewhat similar to the ‘selling yourself’ case you still need to have some track record of your solution/benchmark results, but this might be an easier sell than just your brain … But you’d better do your homework first and make sure that your solution does not exist already. So being innovative and looking into sectors that may not have used data science to the fullest (but also have some appreciation for data to start with) might be a good place to look. Finally - on the homework topic - many solutions do not exist because they are not legal (think HIPPA, privacy, etc.)About the more: Go and build the next Google (that after all was a beautiful piece of data science ….). If I knew how to do it, I would probably not be writing Quora answers.Good luck!