Due to Covid-19, the Fall 2020 ML class is being taught online. To facilitate online teaching, I have begun to create videos for the lectures.
The material in each unit below mostly follows the Powerpoint slides in the lectures, although sometimes the slides have a few more details. To follow the online material:
- Select the unit you want to watch from the list below.
- The presentations in each unit are then divided into sections. In each section, you will find a video, typically 10 to 20 minutes long. Watch the video.
- After most sections, there is a short exercise. Generally, this is a very simple exercise just to emphasize some basic point in the section. Try to do this exercise.
- For most of the exercises, you will find a solution that you can look at to compare your answer against. For others, the solution will be posted in the class website. You do not need to submit answers to any of the questions. But, try to complete the exercise before moving to the next video.
- When you have completed all the sections, there is generally an end-of-unit in-class exercise.
- After completing the end of unit in-class exercise, you will be ready to solve the problems and lab for the unit given in the class syllabus.
If you have any comments / questions, please feel free to put comments below the YouTube video. You can also like the video and subscribe to the channel.
Some videos still being created.
- Unit 1: What is Machine Learning?
- Unit 2: Simple Linear Regression
- This material will be skipped for the graduate students
- Unit 3: Multiple Linear Regression
- Unit 4: Model Order Selection
- Unit 5: LASSO Regularization
- Unit 6: Logistic Regression
- Unit 7: Non-linear Optimization
- Unit 8: SVM
- Unit 9: Neural Networks
- Unit 10: Convolutional and Deep Networks
- Unit 11: PCA
- Unit 12: Clustering