Lesson 6 - Unsupervised Learning and Recommendations
Machine Learning with Python: Zero to GBMs
Course HomeLesson 1 - Linear Regression with Scikit LearnLesson 2 - Logistic Regression for ClassificationAssignment 1 - Train Your First ML ModelLesson 3 - Decision Trees and HyperparametersLesson 4 - Random Forests and RegularizationAssignment 2 - Decision Trees and Random ForestsLesson 5 - Gradient Boosting with XGBoostCourse 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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