stratzilla/AI-ML-tutorials
A collection of artificial intelligence and machine learning tutorials
This collection of Jupyter Notebooks provides step-by-step guidance on implementing various machine learning and artificial intelligence algorithms from scratch. It takes you from a conceptual understanding to a working Python implementation for tasks like optimization and classification. This is for anyone interested in understanding the foundational mechanics of AI/ML algorithms without relying on high-level libraries.
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Use this if you are a student, researcher, or practitioner who wants to deeply understand how core AI/ML algorithms like genetic algorithms, particle swarm optimization, and neural networks function internally.
Not ideal if you are looking for ready-to-use solutions with popular machine learning libraries like scikit-learn or TensorFlow for rapid application development.
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Jupyter Notebook
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GPL-2.0
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Last pushed
Apr 17, 2021
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