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NumPy_Fundamentals: A self-contained Jupyter notebook that teaches NumPy from first principles, covering arrays, vectorisation, broadcasting, and linear algebra, then builds up to training a neural…
A beginner-friendly Jupyter notebook that trains a PyTorch neural network to recognise handwritten MNIST digits, with an interactive canvas to draw and correct your own digits. Includes step-by-ste…
A beginner-friendly Jupyter notebook that trains a neural network to recognise handwritten digits using TensorFlow and Keras. Covers the full ML workflow with plain-English explanations, a drawing …
A hands-on Jupyter notebook teaching scikit-learn from first principles: hand-written k-NN, preprocessing, pipelines, and cross-validation, ending in a neural-network capstone on real handwritten d…
Classical AI in Python: an expert system with certainty factors, a semantic network, Prolog logic, A* and other search algorithms, minimax with alpha-beta, map colouring as a CSP, a STRIPS planner,…
Machine learning from first principles: the ML workflow, linear and logistic regression, trees and ensembles, k-NN, SVM, naive Bayes, k-means, PCA, overfitting, honest evaluation, an end-to-end pip…
Jupyter Notebook
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