Thanks for the analysis. Can't say I understood much, but the concept of automating venture investment is an interesting idea. As a side question, what would you recommend a total beginner to learn if they wanted to go from 0 to being competent at neural networks, or machine learning in general. I'm currently dabbling with R in grad school (biology), and I know Python is big within the machine learning world.
Is there a pathway you would recommend (e.g., first learn Python until you're familiar in X, Y, Z, then make sure to learn the required mathematics... etc)? Also, how long would this process of learning roughly take? Been thinking of potentially changing fields after grad school, or maybe working at the intersection of ML and medicine.
I got started with Andrew Ng's Coursera ML course in 2012, and have been learning ML ever since. I think a very diligent student could catch up in half the time (about 5 years).
Is there a pathway you would recommend (e.g., first learn Python until you're familiar in X, Y, Z, then make sure to learn the required mathematics... etc)? Also, how long would this process of learning roughly take? Been thinking of potentially changing fields after grad school, or maybe working at the intersection of ML and medicine.