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Is there a specific field of research you are trying to get into? If so, pick a research paper/topic with practical industry applications, then implement and ex
by dennybritz 11y ago
Is there a specific field of research you are trying to get into? If so, pick a research paper/topic with practical industry applications, then implement and explain it in an easy-to-understand way. You can write a blog post (or series) about it and publish everything on Github. It may take a while, but personally I found that trying to explain a complex topic in a simple and practical way is the absolute best way to really understand it. Passively reading papers is not going to give you the same understanding. And using JS for this type of project is perfect, because lots of people are familiar with it. You will make research more accessible to everyone, which is something we need. Try to choose a project that's a good fit for JS. For example, something that heavily relies on optimized memory allocation and GPU operations probably isn't a good fit.
Be warned though, there are quite a few research papers, especially those coming out of Academia as opposed to industry, that are cryptic, lacking in detail, or not easily reproducible. And that's intentional. This isn't obvious when you read a paper, it will only become obvious when you actually try to reproduce it. These papers are the result of misaligned goals Academia in, where it's all about publishing as many papers as possible that look good on the surface. When In doubt, I'd recommend focusing on research that has a lot of interest from the industry. That's usually a safer bet.
- gamekathu 11y agospecific field would be machine learning. I regularly follow Karpathy's blog and his convnetjs library [1], and also Harthur's brain library [2]. yes, I also found a lot of papers cryptic and hard to follow [1] https://github.com/karpathy/convnetjs https://github.com/karpathy/convnetjs [2] https://github.com/harthur/brain https://github.com/harthur/brain
- polakallen 11y agoWhat have you done so far in terms of learning machine learning? There's quite a few resources for getting a good foundation, if that's something you might need. Ironically, looking dennybritz's comment, JS is particularly ill-suited for this, as, as far as I'm aware, there are no libraries for working on the GPU, which is tremendously useful for working with machine learning algorithms which usually are crunching lots of data. However, I don't know much about karpathy's specific implementation and experiments, so there might be a reason he choose JS. I'm thinking its more likely to make visualizations easier rather than any computational reason though, so you might be stuck in a niche there.
- gamekathu 11y agoyep I am learning machine learning from Andrew Ng's coursera offering, which is quite good and hence sparked my interest in this field. also, i read few interesting blogs related to neural nets and machine learning to gain further info
- dennybritz 11y agoYou're right that JS is pretty ill-suited for implementing production-level Deep Learning architectures that operate on a lot of data, I think it's still well suited for explaining the concepts in a clear way. A lot of the models have intuitive (and visual) interpretations, something that can be nicely visualized with JS. As for Karpathy's implementation, you're right, he chose JS for that reason. His library is meant as a tool for experimenting and teaching, not to deploy these models in production. Op: Send me an email if you're interested in this (email in profile). I actually started something similar just recently at http://www.wildml.com/ http://www.wildml.com/.
- gamekathu 11y agoNice blog! Yes I am interested in Deep learning, although am just a newbie. Right now I just read around in several blogs to get the idea. As for JS visualizations, TonicDev[1] is a nice option if someone wants a IPython style notebook in JS [1] https://tonicdev.com https://tonicdev.com