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What is AI vs ML: Key Differences Explained about?
This document provides guidelines for a machine learning course. It introduces key machine learning concepts and algorithms including supervised and unsupervised learning, naive Bayes classification, linear regression, logistic regression, regularization, and neural networks. It recommends software tools for machine learning and linear algebra. It also outlines a 60 lecture practical lab covering tasks from basic programming to implementing machine learning algorithms to solve problems using datasets.
- Author
- preethinanjundan
- Language
- EN