Fall 2023 Schedule

Advanced Machine Learning

# date topic description
1 26-Aug-2024 Introduction and Introductions
2 28-Aug-2024 Recap of Linear Algebra and ML Math
02-Sep-2023 Labor Day Holiday
3 04-Sep-2024 Foundations of Learning
4 09-Sep-2024 PAC Learning
5 11-Sep-2024 Linear Learning Models
6 16-Sep-2024 Principal Component Analysis
7 18-Sep-2024 Curse of Dimensionality
8 23-Sep-2024 Bayesian Decision Theory
9 25-Sep-2024 Parameter Estimation: MLE
10 30-Sep-2024 Parameter Estimation: MAP+Naive Bayes
11 02-Oct-2024 Logistic Regression
12 07-Oct-2024 Kernel Density Estimation
13 09-Oct-2024 Support Vector Machines
14 14-Oct-2024 Matrix Factorization
15-Oct-2023 midpoint
15 16-Oct-2024 Stochastic Gradient Descent
16 21-Oct-2024 K-means clustering
17 23-Oct-2024 Expectation Maximization
# date topic description
18 28-Oct-2024 Automatic Differentiation
19 30-Oct-2024 Nonlinear Embedding Approaches
20 04-Nov-2024 Model Comparison I
21 06-Nov-2024 Model Comparison II
22 11-Nov-2024 Model Calibrarion
23 13-Nov-2024 Convolutional Neural Networks
24 18-Nov-2024 Word Embedding