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Algorithms and Models Implementation for introductory courses to Machine Learning. Features Linear Regression, K-Nearest Neighbor, Linear Classifier with Logistic Regression, SVM, NeuralNet and Reinforcement Learning.

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Foundation-MachineLearning

Algorithms and Models Implementation for introductory courses to Machine Learning. Features Linear Regression, K-Nearest Neighbor, Linear Classifier with Logistic Regression, SVM, NeuralNet and Reinforcement Learning.

Note: Some codes in this repository is developed by faculty members at the University of Toronto. Commercial redistribution is strictly forbidden.

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Algorithms and Models Implementation for introductory courses to Machine Learning. Features Linear Regression, K-Nearest Neighbor, Linear Classifier with Logistic Regression, SVM, NeuralNet and Reinforcement Learning.

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