Engineering / College · Machine Learning

Machine Learning Fundamentals Notes – Regression, Classification, Evaluation and Neural Networks

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Machine Learning notes for 5th semester B.Tech CSE (AI and ML) students. Covers types of learning, the ML workflow, linear and logistic regression with gradient descent, decision trees with entropy and information gain, k-nearest neighbours, Naive Bayes, support vector machines, k-means clustering and PCA, bias–variance trade-off, regularisation, evaluation metrics such as precision, recall and F1, cross-validation, and an introduction to neural networks and backpropagation, with worked examples and exam questions.