nucs349.github.io

Class Calendar

This is a prediction of what will be covered each week, but the schedule is subject to change (hopefully none or minimal) as the course progresses.

Week of Day Lecture Topic (Click for recording) Homework Due (Days from lecture to homework)
14-Sep Mon [Classes begin Wednesday, 9/16]  
  Wed Intro to Class  
  Fri Intro to ML  
21-Sep Mon Intro to ML (continued) HW0 - Setup (5 days)
  Wed Decision Trees  
  Fri Decision Trees (continued)  
28-Sep Mon Probability  
  Wed Bayes’ Theorem  
  Fri Naive Bayes, MAP, and MLE  
5-Oct Mon Measuring Distance  
  Wed k-Nearest Neighbors  
  Thu   HW1 - Decision Trees (13 days)
  Fri Collaborative Filtering  
12-Oct Mon k-Means Clustering  
  Wed Gaussian Mixture Models  
  Thu   HW2 - Measuring Distance, k-Nearest Neighbors (8 days)
  Fri Gaussian Mixture Models (continued)  
19-Oct Mon Linear Regression  
  Wed Logistic Regression  
  Thu    
  Fri Support Vector Machines  
  Sat   HW3 - k-Means Clustering, GMMs (8 days)
26-Oct Mon Local Search  
  Wed Gradient Descent, Regularization  
  Thu   HW4 - Linear Regression (6 days due to Friday assignment)
  Fri Genetic Algorithms  
2-Nov Mon Boosting  
  Wed Crowd Sourcing, Active Learning  
  Thu    
  Fri Reinforcement Learning HW5 - Gradient Descent, Regularization (9 days)
9-Nov Mon [Lecture cancelled]  
  Wed Reinforcement Learning (continued) + Perceptrons recorded outside of class  
  Thu    
  Fri Neural Networks, Deep Learning  
16-Nov Mon Probability Density Function + Much More on MLE  
  Wed Experimental Validation  
  Fri Dos and Don’ts of ML, Data Handling and Considerations, and ML in academia vs. ML in the industry + Review or general discussion about ML and AI  
23-Nov Mon Q&A about Final (Final moved to 7-Dec, during Exam Week) HW6 - Reinforcement Learning (12 days) + HW7 - Neural Networks, Deep Learning (9 days)
  Tue   HW8 - Presentation of a Research Paper (not tied to a lecture (Presentation not live; due on Canvas as short video)
  Wed [Thanksgiving holiday begins]  
  Fri [Thanksgiving holiday continues]  
30-Nov Mon Review or general discussion about ML and AI  
1-Dec Wed [Last day of classes, but we don’t have class]  
7-Dec Tue Final (Exam 3PM - 5 PM on Canvas while being on Zoom OR project due OR video of paper presentation due)