ECE365: Fundamentals of Machine Learning (Labs and Quizzes)
| Topic | Sample Quiz | Quiz Answer | Feedback for Quiz | Lab | Due |
| Week 1 | Introduction to Python | No Quiz | No Quiz | No Quiz | [link] | Not to be graded |
| Week 2 | Classification, Part 1 | [link] | [link] | | [link] | 5th Feb, 11:59pm |
| Week 3 | Classification, Part 2 | [link] | [link] | | [link] | 12th Feb 11:59pm |
| Week 4 | Linear Regression and Clustering | [link] | [link] | | [link] | 19th Feb 11:59pm |
| Week 5 | Principal Component Analysis | [link] | | | [link] | 26th Feb 11:59pm
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Quizzes will be conducted in class, not in lab sessions.
Upload Lab assignments(just notebooks) with file name as your netid on Compass.
Lab 1
Hints:
Exercises 5 and 6 will be building blocks for the first problem in Lab 2 (where you can use part (a) or part (b) of both exercises). You should be able to do part (a) of both exercises in a straightforward manner. As stated in the lab, part (b) is optional, but good to know. If you're stuck on part (b), make sure to write out the matrices and you should be able to construct the appropriate matrix multiplication. If you do not solve part (b), do not worry about it. But, you really should solve part (a) of both Exercises 5 and 6.
A better hint for Exercise 6(b) might be: “You can do this with the np.dot, elementwise multiplication and np.sum (along an axis) operations.â€
Please follow the Python instructions to get started with Jupyter notebooks. You should not need to install any additional packages for this portion of the course if you have installed Anaconda or Canopy.
The following other Python tutorials may be helpful:
And a few links to write code concisely:
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