Welcome to Machine Learning in Computational Biology! This GitHub Repository will contain all the homework and the solutions to the homework (after the deadline of the homework has been changed). Please submit all your programs to Gradescope for the autograder to test and run your programs.
- Homework 1: linear algebra & probability due 1/31
- Homework 2: simulations, Python practice, and Gaussian Discriminant Analysis due 2/6
- Homework 3: E&M algorithm, K-Means (optional), and Markov modeling due 2/13
- Homework 4: ML functions and linear gradient descent due 2/27
- Homework 5: forward and back-propagation practice and PyTorch tutorial due 3/6
- Homework 6: convolutional neural network practice and tutorial due 3/13
- Homework 7: tSNE implementation due 3/20
Software/Python package requirements:
- Python 3.x
- scikit-learn
- NumPy
- SciPy
- Pandas
- Matplotlib
- PyTorch (Homework 5 and beyond)
If you have Python already installed, you can simply install the packages by running this command in your terminal:
pip3 install sklearn numpy scipy pandas matplotlib
Course instructor: Liana Lareau
Course Reader & Homework author/maintenance: Yorick Chern