1. Clarify your goal. Do you want to: a) Become an academic in mathematics/statistics. b) Become an academic in computer science with a focus on artificial i

1. Clarify your goal. Do you want to: a) Become an academic in mathematics/statistics. b) Become an academic in computer science with a focus on artificial intelligence. c) Become a MLE in "regular" statistical applications. Aka bayesian classification, "core" statistical principles. d) Become a specialized computer vision/natural language processing focused MLE. e) Become a generalist software engineer who can whip out the above if needed. In no way is e) the inferior option. Generalists who can write code fast with 100% test coverage and pristine logging are by far the segment the industry has the shortest supply of. There are TONS of math guys. Vanishingly few Principal Engineers who can write a design document and lead a project. (Machine learning customers are OBSESSED with test coverage and verifiability. Believe it or not, multinational corporations generally don't want to unleash a {your_adjective_here}ist algorithm on the world.) 2. Study the above, properly. To study the math, Elements of Statistical Learning/Algorithms by Goodfellow. Start on page 1, do every second exercise. Publish a summary of every chapter you finish with your answers to GitHub. 3. Pursue your goal in a publicly verifiable manner. See: https://news.ycombinator.com/item?id=32071137 https://news.ycombinator.com/item?id=32071137