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Lesson 6 - Unsupervised Learning and Recommendations

Machine Learning with Python: Zero to GBMs

Lesson 1 - Linear Regression with Scikit Learn Lesson 2 - Logistic Regression for Classification Assignment 1 - Train Your First ML Model Lesson 3 - Decision Trees and Hyperparameters Lesson 4 - Random Forests and Regularization Assignment 2 - Decision Trees and Random Forests Lesson 5 - Gradient Boosting with XGBoost Course Project - Real-World Machine Learning Model

This lesson covers the following topics:

Overview of unsupervised learning algorithms in Scikit-learn
Clustering algorithms: K Means, DBScan, Hierarchical clustering, etc.
Dimensionality reduction (PCA) and manifold learning (t-SNE)
Creating a recommender system using collaborative filtering

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