- HW 1: Bayes Theorem, Min Error Rate Classifier, Application for Computer Vision (hw1.ipynb.zip): Due: September 19, 2024
- HW 2: Multi-Layer Perceptron: (hw2.ipynb.zip): Due: October 10, 2024
- HW 3: A Deeper Multi-Class MLP (hw3.ipynb.zip): Due October 22, 2024
- HW 4: Getting Deeper with Digits: LeNet (hw4.ipynb.zip): Due October 31, 2024
- HW 5: Domain Transfer and Fine-Tuning (hw5.ipynb.zip): Due November 12, 2024
- Project Proposal (final_project.ipynb.zip): Due November 5, 2024
- Project Report and Presentation (schedule for presentations): Due December 9, 2024
- Regrading Requests: (regrading request template). Regrading requests can be made within one week of an assignment being returned. Regrading requests cannot be made for assignments that were handed in late. To request a regrade, please fill out the template in the link above, attend any TAs office hours, and present your request. Please note: the regrading TA may deduct more points than you originally received if omissions were made in the initial grading or if the initial grading was overly lenient.
Software Resources (all one Google search away...):
- Python
- Jupyter Notebook
- Pytorch
- Tensorflow
Background on Deep Learning:
Background on Old-School Computer Vision:
Google Cloud :
GENERAL INSTRUCTIONS: TBA
- Deep Learning, Goodfellow, Bengio, and Courville
- Stanford Deep Learning Course (CS231n)
- Understanding LSTM Networks, Colah
- Yes, You Should Understand Backprop, Karpathy
- Tensorflow Tutorial
- Keras
Background on Old-School Computer Vision:
- Computer Vision: A Modern Approach, Forsyth and Ponce
- Computer Vision: Algorithms and Applications, Richard Szeliski
- Receptive Fields, Binocular Interaction, and Functional Architecture in the Cat's Visual Cortex, Hubel and Wiesel, 1962
- Hubel and Weisel, Cat Experiments Video
- MIT Summer Vision Project, Papert, 1966
- Vision, Marr, 19
- Computer Vision, Ballard and Brown, 1982
- Robot Vision, Horn, 1985
- Pattern Classification, Duda, Hart, and Stork
- Pegasos: Primal Estimated sub-Gradient Solver for SVM, Shalev-Shwartz et al.
Google Cloud :
GENERAL INSTRUCTIONS: TBA