This is an introductory twelve lesson Machine Learning course (2 hours each) from the University of San Francisco for people that have experience in programming. Contents: Lesson 1: Introduction to Random Forests Lesson 2: Random Forest Deep Dive Lesson 3: Performance, Validation and Model Interpretation Lesson 4: Feature Importance, Tree Interpreter Lesson 5: Extrapolation and RF from scratch Lesson 6: Data Products and Live coding Lesson 7: RF from scratch an Gradient Descent Lesson 8: Gradient Descent and Logistic Regression Lesson 9: Regularization, Learning Rates and NLP Lesson 10: More NLP and Columnar Data Lesson 11: Embeddings Lesson 12: Complete Rossmann, Ethical issues Please go to the course website to watch all lessons.

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