# Course Schedule

wk | Lecture | Notes | Links | Reading material |
---|---|---|---|---|

9/1 | Building Machine that 'learn' | |||

9/6 | Essential Math and Formalism for ML | HW1 Release (Math Foundations for ML) | ||

9/8 | Philosophical and Cognitive underpinnings of ML | |||

9/13 | Linear Regression and Regularization (Part 1) | |||

9/15 | Linear Regression and Regularization (Part 2) | |||

9/20 | Logistic Regression (Part 1) | HW 1 Due HW2 Release (Linear Regularization) | ||

9/22 | Logistic Regression (Part 2) | |||

9/27 | Support Vector Machines (Part 1) | |||

9/29 | Support Vector Machines (Part 2) | |||

10/4 | Decision Trees for Classification | HW 2 Due HW3 Release (SVMs) | ||

10/6 | Random Forests for Classification | |||

10/13 | Non-Linear Regression and Gradient Descent | |||

10/18 | Gradient Descent and its Variants | HW 3 Due HW4 Release (Random Forests) | ||

10/20 | Perceptrons (Part 1) | |||

10/25 | Perceptrons (Part 2) | Capstone Project Released | ||

10/27 | Convolutional Neural Networks (Part 1) | |||

11/1 | Convolutional Neural Networks (Part 2) | |||

11/3 | Recurrent Neural Networks (Part 1) | HW 4 Due HW5 Release (CNNs) | ||

11/8 | Recurrent Neural Networks (Part 2) | |||

11/10 | Dimensionality Reduction (Part 1) | |||

11/15 | Dimensionality Reduction (Part 2) | |||

11/17 | Clustering (Part 1) | HW 5 Due HW6 Release (Dimension reduction) | ||

11/22 | Clustering (Part 2) | |||

11/29 | Reinforcement Learning Foundations (Part 1) | |||

12/1 | Reinforcement Learning Foundations (Part 2) | |||

12/6 | Policy Gradients | |||

12/8 | Frontiers of ML (research discussions by members of CILVR) | |||

12/13 | Frontiers of ML | |||

12/14 | Capstone Project Due |