Crash Course In Machine Learning Part 3 - Unsupervised Learning

In part 3 of our crash course, we get a bird's eye view of unsupervised learning.

This is really useful when you have data that you think should fall neatly into groups, but they are described by hundreds of different parameters.

The K means algorithm and/or principle component analysis can really help you see through all the haze and get something meaningful from your data.

Learn how to turn deep reinforcement learning papers into code:

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Deep Q Learning:

Actor Critic Methods:

Curiosity Driven Deep Reinforcement Learning

Natural Language Processing from First Principles:
Reinforcement Learning Fundamentals

Here are some books / courses I recommend (affiliate links):

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