UofT-DSI | deep_learning - Assignment 2#93
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ajharris wants to merge 33 commits intoUofT-DSI:mainfrom
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…pant' and downgrade Python version to 3.10.17 Build venv in uv instead of conda
…mender Systems - Created Module 1: Introduction to Deep Learning with an overview, applications, and course outline. - Added Module 2: Neural Networks and Backpropagation covering key concepts like activation functions, loss functions, and optimization tricks. - Introduced Module 3: Recommender Systems & Embeddings, discussing embeddings, dropout regularization, and ethical considerations in recommendation algorithms.
…t encoding explanation - Adjusted execution counts in lab_2.ipynb to reflect the correct order of cell execution. - Added a new markdown file explaining the relationship between identity matrices, one-hot encoding, and embedding lookups, including TensorFlow optimizations for efficient row selection.
…ng key concepts and insights
Corrected formatting of the identity matrix example in module 2 summary.
…rning into assignment-one
…l Networks - Introduced slides_part1.m4a and slides_part1.txt covering the fundamentals of CNNs, including convolutions, pooling, and architectures like VGG and ResNet. - Added slides_part2.m4a and slides_part2.txt focusing on transfer learning, data augmentation, regularization techniques, and modern architectures.
…n counts, and add print statements for clarity. Add TensorFlow CPU environment setup documentation for reproducibility on macOS Intel.
Update from DSI
Created using Colab
Created using Colab
Created using Colab
Removed Colab-specific metadata from the notebook.
Created using Colab
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