Teaching modules built in Python (and potentially expanded) to help step-by-step explain basic concepts up towards modern day techniques and problems.
For contributions please follow standard open source guidelines and issue pull requests. There is no guarantee regarding time to accept requests as this repository is maintained by one person.
See each sub-component for a readme regarding the specific topic. Many of these topics are incredibly broad and thus cannot be incompassed in a single README nor even in a single project. The purpose here is just to introduce core concepts used throughout System Identification and Machine Learning.
- Basics
- Calculus
- Linear Algebra
- Statistics
- Beginner
- Information Theory
- Parameter Estimation
- Shallow Algorithms (White Box Models)
- Intermediate
- Perceptrons (MLPs)
- Signal Processing
- Advanced
- Deep Learning
- Nonlinear Systems
- Experimental
- eXplainable Aritifical Intelligence
- Simulated Based Inferencing - SBI