Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms.
My Spark AR Studio Development Tests – Part 1.
This is an amazing set of Kubernetes learning materials and tutorials from Microsoft, published in 2018. It's full of videos and a minor amount of reading. You can probably blow...
https://github.com/abhat222/Data-Science--Cheat-Sheet If there's anything we could use every now and then it's a good cheat sheet. After years of programming there are so many things you learn with every new...
This is a great site for learning about how companies are using different Amazon Web Services to accomplish their application goals. It's all about architecture and getting ideas for different...
