About
Who writes here, and why.
Hi — I’m Majid Mazouchi. This is my working notebook on control and machine learning — the engineering stack that sits under autonomous systems. My professional page is at majid-mazouchi.github.io.
I started this because the internet has great resources on each of these topics in isolation, but surprisingly little that sits at the intersection. A PID tutorial won’t tell you how reinforcement learning relates to it. A deep learning course won’t tell you why the stability arguments you see in an LQR derivation matter when you’re training a controller with PPO.
Everything here is written in the spirit of a good lab notebook: show the math, show the code, show what actually happened when you ran it.
What you’ll find
- Control Systems — classical and modern control theory, worked through with examples.
- Motor Control — driving DC, BLDC, and stepper motors, plus the sensors and electronics around them.
- Machine Learning — the classical ML toolkit, with a bias toward problems in signal processing and dynamics.
- Neural Networks — architectures and training, especially where they overlap with system identification and control.
- Reinforcement Learning — policy optimization, actor-critic methods, and how they connect to adaptive and optimal control.
Contact
Drop me a line at Majid.Mazouchi@gmail.com or open an issue on the GitHub repo.
Colophon
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