This repository contains assignments for the course DSAIT4005 Machine and Deep Learning in TU Delft, a newly formed course derived from the original CS4220 Machine Learning 1 and CS4240 Deep Learning. The course covers a wide range of topics in machine learning and deep learning, providing both theoretical and practical insights into these fields.
Each assignment folder includes three files:
Assignment_*_template.ipynb: The starter notebook, provided as a blank template for students to complete.Assignment_*.ipynb: The primary notebook file, with my own completed solution.Assignment_*_SOLUTIONS.ipynb: A reference solution with completed answers, for comparison and review.
Here is a list of the assignments, along with their respective topics. You can click the links below to open the corresponding Jupyter Notebook files directly in Jupyter nbviewer.
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Assignment 1: Introduction
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Assignment 2: Discriminative Classifiers
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Assignment 3: Neural Networks
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Assignment 4: Backpropagation
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Assignment 5: Optimization
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Assignment 6: Evaluation
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Assignment 7: Complexity and SVM
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Assignment 8: Convolutional Neural Networks (CNN)
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Assignment 9: Regularization
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Assignment 10: Recurrent Neural Networks (RNN)
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Assignment 11: Self-Attention
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Assignment 12: Unsupervised Learning
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DL Lab Review: A personal review notebook created for DL coding preparation, especially useful for exam revision.
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Pytorch Tensors: A Small Intro (for Assignment 3): A recommended tutorial in Assignment 3, providing an introduction to PyTorch tensors.