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Linear Regression: An Introduction A Warm-up Example Using Linear Regression for Sentiment Prediction Importance of Featurization Linear Regression in Programming Statistical Learning: What It Means to Learn A Warm-up Example Summary of Statistical Learning Implications for Applications of Machine Learning Optimization via Gradient Descent Gradient Descent Implications of Linearity of Gradient Regularizers Gradient Descent in Programming Linear Classification General Form of a Linear Model Logistic Regression Support Vector Machines Multi-class Classification (Multinomial Regression) Regularization with SVM Linear Classification in Programming Exploring ``Data Science'' via Linear Regression Boston Housing: Machine Learning in Economics fMRI Analysis: Machine Learning in Neuroscience Unsupervised Learning Clustering Unsupervised Learning Clustering k-Means Clustering Clustering in Programming Low-Dimensional Representation Low-Dimensional Representation with Error Application 1: Stylometry Application 2: Eigenfaces n-Gram Language Models Probabilistic Model of Language n-Gram Models Start and Stop Tokens Testing a Language Model Matrix Factorization and Recommender Systems Recommender Systems Recommender Systems via Matrix Factorization Implementation of Matrix Factorization Deep Learning Introduction to Deep Learning A Brief History Anatomy of a Neural Network Why Deep Learning? Multi-class Classification Feedforward Neural Network and Backpropagation Forward Propagation: An Example Forward Propagation: The General Case Backpropagation: An Example Backpropagation: The General Case Feedforward Neural Network in Programming Convolutional Neural Network Introduction to Convolution Convolution in Computer Vision Backpropagation for Convolutional Nets CNN in Programming Reinforcement Learning Introduction to Reinforcement Learning Basic Elements of Reinforcement Learning Useful Resource: MuJoCo-based RL Environments Illustrative Example: Optimum Cake Eating Markov Decision Process Markov Decision Process (MDP) Policy and Markov Reward Process Optimal Policy Reinforcement Learning in Unknown Environment Model-Free Reinforcement Learning Atari Pong (1972): A Case Study Q-learning Applications of Reinforcement Learning Deep Reinforcement Learning Advanced Topics Machine Learning and Ethics Facebook's Suicide Prevention Racial Bias in Machine Learning Conceptions of Fairness in Machine Learning Limitations of the ML Paradigm Final Thoughts Deep Learning for Natural Language Processing Word Embeddings N-gram Model Revisited Mathematics for Machine Learning Probability and Statistics Probability and Event Random Variable Central Limit Theorem and Confidence Intervals Final Remarks Calculus Calculus in One Variable Multivariable Calculus Linear Algebra Vectors Matrices Advanced: SVD/PCA Procedures