This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

Sequential decision-making under uncertainty is a foundational topic in multiple fields - including economics, operations research, and computer science, built around the foundation of Markov decision ...

How to become a machine learning engineer: A cheat sheet Your email has been sent If you are interested in pursuing a career in AI and don't know where to start, here's your go-to guide for the best ...

A language that requires less rigid coding on the part of the programmer. It typically features "dynamic typing," which gives the programmer more freedom to pass parameters at runtime without having ...

Dynamic programming algorithms are a good place to start understanding what's really going on inside computational biology software. The heart of many well-known programs is a dynamic programming ...