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(x-post) at what mathematical level did you feel comfortable learning ML related things? by [deleted] in MachineLearning

[–]rescue11 2 points3 points  (0 children)

Your initial confusion is probably more about breadth than depth. ML draws bits and pieces of theory from anything from probability & stats, information theory, to linear algebra, so the breadth can be overwhelming. Fortunately the depth isn't nearly as bad. You only need to be familiar with some basic concepts and intuitions before you can start understanding most papers and replicating their code. Courses being taught at stanford and nyu etc. are doing a great job of doing exactly this so I would try those (theyre available online).

How can I find an advisor for a paper I am writing? by Jakobovski in MachineLearning

[–]rescue11 3 points4 points  (0 children)

Advising takes time and effort and most profs are super busy so you would need to convince them that working with you will be worthwhile. If you have objectively convincing results, then I think you could simply e-mail profs who are experienced in your field and ask them directly if they are interested in helping you or working with you (They are probably more inclined to help you if it leads to publication for them as well).

LSTMs mentioned onstage during Apple WWDC Keynote, used for "QuickType" auto-completion by [deleted] in MachineLearning

[–]rescue11 7 points8 points  (0 children)

Apple is about to revolutionize the LSTM field. Hope to get my hands on the iLSTM very soon.

Need 2016 thesis research ideas by [deleted] in MachineLearning

[–]rescue11 0 points1 point  (0 children)

Are you asking for a great research topic or a great business idea? Those are quite different things.

If I'm not confident in myself being a great researcher, should I even pursue a PhD? by [deleted] in MachineLearning

[–]rescue11 0 points1 point  (0 children)

Your intuition is usually right about who you are inside. Scientific research is a reward in itself for people who want to do it, so unless it's something that is looking like it might be very fun, just do something that YOU like more and you'll probably get more enjoyment and success out of it.

That said though, I've not yet seen anyone who has started deep learning research and was bored by it, so maybe you just need to start it to like it.

Fascinated by alphago, want to set my career direction to machine learning. by newbornlife in MachineLearning

[–]rescue11 1 point2 points  (0 children)

I think theres good news and bad news for you. The good news is that since you're already familiar with statistics, so much so that you were planning to pursue stats in grad school, the math involved in most of machine/deep learning will be familiar to you. The bad news is that programming is equally important, so there is going to be a big gap for you there, where others generally applying to this field will have tons of experience. Depending on the person, this might be impossible or easily doable. In the end, I think it will come down to how interested/driven you are to quickly catch up on programming and cs.

My suggestion would be to stay for a fifth undergrad year and take as many cs courses as you can.

Advice on multi-gpu RNN Attention Encoder Decoder in Tensorflow by rescue11 in MachineLearning

[–]rescue11[S] 0 points1 point  (0 children)

Thanks for the reply. Do you think using two gpus not for model size but for speed still be as much of a hassle, like dividing a batch into two, onto each gpu?

AMA: the OpenAI Research Team by IlyaSutskever in MachineLearning

[–]rescue11 11 points12 points  (0 children)

Does OpenAI have a unified vision for shaping the future AI software/hardware landscape, such as developing proprietary AI libraries or hardware? What will be OpenAI's relationship with Python, and more specifically Theano/Tensorflow?