Link to videos
Lecture Notes
Module 0: Python programming
2021-08-16, Lecture 1: Kaggle Notebook.
2021-08-18, Lecture 2: Kaggle Notebook. Inner product diagram.
2021-08-20, Lecture 3: Kaggle Notebook. Perceptron. (Updated version extending the notebook and transcript from the previous class).
2021-08-23, Lecture 4: Kaggle Notebook. (Updated version extending the notebook from the previous class). Kaggle Notebook on Numpy indexing.
2021-08-25, Lecture 5: Kaggle Notebook on Perceptron, updated version extending the notebook from the previous class. Kaggle Notebook for review of basic Python programming.
2021-08-27, Lecture 6: Kaggle Notebook for review of basic Python programming (updated from last class): basic dynamic programming.
2021-08-30, Lecture 7: Kaggle notebook, linear systems and the singular value decomposition.
Module 1: Probability and Statistics
2021-09-01, Lecture 8: Slides, Basic Probability, Counting, Conditional Probability, Independence and Bayes Theorem.
2021-09-06, Lecture 9: Slides, Random Variables, Joint and Marginal Distributions, Distribution Functions - PDFs and CDFs.
2021-09-08, Lecture 10: Slides, Mean, Variance, Covariance, Conditional Expectation and properties of some well known distributions.
2021-09-13, Lecture 11: Slides, Central Limit Theorem, Law of Large Numbers, Confidence Intervals.
2021-09-15, Lecture 12: Slides, Point Estimators, Confidence Intervals with t-distribution, Method of Moments, Maximum Likelihood Estimator, Bayesian Estimator.
2021-09-20, Lecture 13: Slides, Simulation & Hypothesis Testing; Dice Roll Simulation; Queuing Simulation.
Module 2: Supervised Learning / Deep Learning
2021-09-22, Lecture 14: Slides, Various Paradigms of Machine Learning
2021-09-27, Lecture 15: Slides, Fundamentals of Supervised Learning.
2021-09-29, Lecture 16: Slides, Classification.
2021-10-04, Lecture 17: Kaggle Notebook, Programming Tutorial on Logistic Regression.
2021-10-06, Lecture 18: Slides, Introduction to Deep Learning.
2021-10-11, Lecture 19: Slides, Gradient Descent, Backpropagation, Neural Network Zoo
2021-10-13, Lecture 19: Slides, Neural Network Zoo, VAEs, GANs
2021-10-18, Lecture 20: Kaggle Notebook for Data Exploration and CNN, Kaggle Notebook for Autoencoder
Module 2: Unsupervised Learning;...
2021-10-20, Lecture 21: Slides, Clustering: K-means
2021-10-25, Lecture 22: Slides, Hierarchical clustering
2021-10-27, Lecture 23: Slides, Spectral clustering. For more on clustering click here
2021-11-01, Lecture 24: Slides, GMM & EM
2021-11-03, Lecture 25: Slides, Factor Analysis (Section 12.1.5 of this book)
2021-11-08, Lecture 26: Slides, PCA
2021-11-10, Lecture 27: Slides, FA, CCA and ICA (Section 12.6 of this book for ICA)
2021-11-12, Tutorial: Kaggle Notebook, Tutorial on Principal Component Analysis and Dimensionality Reduction
2021-11-15, Lecture 28: Slides, Graphical models