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Module 2 - Supervised models - Supervised Machine Learning in Python

Linear models

Introduction to Linear Regression (3:36)
Linear Regression in Python (6:20)
Introduction to Ridge Regression (4:20)
Ridge Regression in Python (5:34)
Introduction to Lasso Regression (5:15)
Lasso Regression in Python (4:34)
Introduction to Elastic Net Regression (4:43)
Elastic Net Regression in Python (4:07)
Introduction to Logistic Regression for classification (7:22)
Logistic Regression in Python (15:19)
Student quiz

Decision trees

Introduction to decision trees (20:17)
Decision Trees in Python (12:15)
Student quiz

K-nearest neighbors

Introduction to KNN (6:31)
KNN in Python (11:40)
Student quiz

Naive Bayes

Introduction to Naive Bayes (7:07)
Categorical Naive Bayes in Python (6:43)
Bernoulli Naive Bayes in Python (5:09)
Gaussian Naive Bayes in Python (4:22)
Student quiz

Support Vector Machines

Introduction to SVM (6:05)
Linear SVM in Python (7:08)
Non-linear SVM in Python (11:05)
Student quiz

Neural Networks

Introduction to Neural Networks (21:11)
Neural Networks in Python (15:42)
Student quiz

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