# ML Specialization 2022 ## Supervised Learning - Regression, classification ## Neural Networks - Architecture, training ## Unsupervised Learning - Clustering, anomaly detection, recommenders ## Retrieval - KNN, KD-trees, LSH, K-means, LDA

Machine Learning Specialization 2022

Coursera: Machine Learning Specialization (2022)

Download source code and full text of Mind map: GitHub

Course 1: Supervised Machine Learning: Regression and Classification

Week 1: Introduction to Machine Learning
Week 2: Regression with multiple input variables
Week 3: Classification

Course 2: Advanced Learning Algorithms

Week 1: Neural Networks
Week 2: Neural network training

Course 3: Unsupervised Learning, Recommenders, Reinforcement Learning

Week 1-4: Clustering, anomaly detection, recommender systems, reinforcement learning

Course 4: ML Clustering & Retrieval

Case Studies: Finding Similar Documents
K-nearest neighbors, KD-trees, locality sensitive hashing
K-means, expectation maximization (EM), latent Dirichlet allocation (LDA)

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