CS 7641 - All the code
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Jul 6, 2023 - Java
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cs7641
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A collection of study materials for OMSCS CS7641 Machine Learning.
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Sep 24, 2024
CS7641 - Machine Learning - Assignment 4 - Markov Decision Processes
machine-learning algorithm reinforcement-learning q-learning mdp markov-decision-processes omscs policy-iteration value-iteration georgia-tech burlap assignment4 cs7641
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Sep 22, 2025 - Java
Fall 2019 course Machine learning Georgia Tech solutions
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Jan 4, 2020 - Jupyter Notebook
Three optimization problem domains are created and applied to the randomized hill climbing, simulated annealing, genetic and MIMIC randomized optimization algorithms. Also, a neural network implementation is reimplemented using randomized optimization algorithms from the mlrose_hiive Python library.
machine-learning optimization genetic-algorithm jupyter-notebook eight-queen-problem simulated-annealing hill-climbing metaheuristics georgia-tech travelling-salesman-problem mimic cs7641 randomized-optimization four-peaks-problem neural-network-training mlrose
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Sep 28, 2026 - Jupyter Notebook
Two Markov Decision Process (MDP) problems – the Frozen Lake and the Gambler’s Problem MDPs. Policy iteration, value iteration and the Q-Learning reinforcement learning algorithm are implemented on each of the MDPs and are analyzed.
machine-learning reinforcement-learning jupyter-notebook openai-gym q-learning dynamic-programming markov-decision-processes policy-iteration value-iteration gymnasium georgia-tech gambler-problem cs7641 frozen-lake bettermdptools
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Sep 28, 2026 - Jupyter Notebook
Decoupled superpixel clustering + ViT for near real-time semantic segmentation: 53.77% mIoU at 54.8 ms/image on Cityscapes with a frozen ResNet-50 and parameter-free SLIC (Georgia Tech CS 7641, Team 45)
machine-learning computer-vision pytorch semantic-segmentation superpixels slic cityscapes georgia-tech cs7641 vision-transformer
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Jul 21, 2026 - Python
Implementation of unsupervised learning algorithms, namely clustering algorithms and dimensionality reduction algorithms (k-Means, EM clustering, PCA, ICA, random projections and t-SNE) on two datasets - a Rice dataset and a Spambase dataset; exploration of the application of the unsupervised learning algorithms on a neural network implementation.
machine-learning clustering scikit-learn keras jupyter-notebook pca expectation-maximization gaussian-mixture-models dimensionality-reduction kmeans unsupervised-learning tsne georgia-tech ica cs7641 random-projection
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Sep 28, 2026 - Jupyter Notebook
Complex and comprehensive supervised machine learning tasks and analyses by implementing several machine learning models/algorithms (Decision Tree, Neural Network, Gradient Boosting, Support Vector Machine and k-Nearest Neighbor models, each with different hyper-parameters) on two datasets
machine-learning scikit-learn keras jupyter-notebook neural-networks supervised-learning classification decision-trees support-vector-machines knn hyperparameter-tuning gradient-boosting georgia-tech model-comparison cs7641 uci-datasets
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Sep 27, 2026 - Jupyter Notebook
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