A collection of notebooks on Dynamic Systems, Automatic Control, and Reinforcement Learning

Current topics

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Topics in control and machine learning

Imitation Learning	Autoregressive processes	Recurrent networks

PID Control

Dynamic Systems

Moving averages	1D convolutions	Dynamic systems with limited memory

Markov chains and stochastic recurrence relations	Dynamic systems with unlimited memory	Recurrence relations

Data preprocessing and feature normalization

ZCA sphereing

Installation

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To successfully run the Jupyter notebooks contained in this repo we highly recommend downloading the Anaconda Python 3 distribution. Many of these notebooks also employ the Automatic Differentiator autograd which can be installed by typing the following command at your terminal

  pip install autograd

With minor adjustment users can also run these notebooks using the GPU/TPU extended version of autograd JAX.

Creators

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This repository is in active development by Jeremy Watt and Reza Borhani - please do not hesitate to reach out with comments, questions, typos, etc.