This article series can be seen as a developer's guide to learning everything about Artificial Intelligence and Machine Learning.
The series will teach everything in programming terms and try to avoid stupid Maths wherever possible.
There's also an accompanying article series on Medium - though as Medium has not so good code integration capabilities it is recommended to use this repository for reference.
Each chapter also has an /example
folder that contains
the final project that the reader has to build to complete
the chapter for itself.
The philosophy of this article series is mostly something along the lines of "If you haven't coded it, you probably talk bullshit anyways.".
So the reader is highly encouraged to code, build practical projects and to find mistakes my code :)
This chapter also includes a solution.
This chapter also includes a solution.
- Reinforcement Learning Basics
- Backpropagation
- ??? explain quirks of overfitting scenarios
- ??? explain reward hacking
- Pong Game (Homework)
- ANN Design Algorithms
- NEAT
- Species Management
- Genome Pool and Breeding
- NEAT Flappy Plane (Homework)
- HyperNEAT
- ??? explain idea of replacing activation functions
- Genome Representation / Substrates
- ??? explain quirks of dna history analysis
- HyperNEAT Pong Game (Homework)
Examples
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