{"id":20110190,"url":"https://github.com/sudarshanasrao/ee559-machine_learning-usc","last_synced_at":"2026-04-11T09:06:31.591Z","repository":{"id":100988849,"uuid":"594294930","full_name":"SudarshanaSRao/EE559-Machine_Learning-USC","owner":"SudarshanaSRao","description":"USC graduate level Machine Learning course","archived":false,"fork":false,"pushed_at":"2025-01-02T18:02:42.000Z","size":7889,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-01-13T05:41:54.778Z","etag":null,"topics":["cnn","keras","machine-learning","neural-networks","numpy","python","scikit-learn","scipy","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/SudarshanaSRao.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-01-28T04:47:12.000Z","updated_at":"2025-01-02T18:02:46.000Z","dependencies_parsed_at":null,"dependency_job_id":"9a966ea2-bda2-42b6-9cde-991185be8bda","html_url":"https://github.com/SudarshanaSRao/EE559-Machine_Learning-USC","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SudarshanaSRao%2FEE559-Machine_Learning-USC","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SudarshanaSRao%2FEE559-Machine_Learning-USC/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SudarshanaSRao%2FEE559-Machine_Learning-USC/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SudarshanaSRao%2FEE559-Machine_Learning-USC/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SudarshanaSRao","download_url":"https://codeload.github.com/SudarshanaSRao/EE559-Machine_Learning-USC/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241550391,"owners_count":19980719,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cnn","keras","machine-learning","neural-networks","numpy","python","scikit-learn","scipy","tensorflow"],"created_at":"2024-11-13T18:10:52.279Z","updated_at":"2025-10-08T13:28:10.930Z","avatar_url":"https://github.com/SudarshanaSRao.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# EE559--Machine-Learning\nWelcome to the repository for my **Machine Learning (EE-559)** assignments! This repository contains all my solutions to the assignments in the course, focusing on classic machine learning algorithms and deep learning using **TensorFlow** and **Keras**. Each assignment demonstrates my ability to implement and apply machine learning models, handle datasets, preprocess data, and evaluate the performance of models using various metrics.\n\n## Key Techniques\n1. **Supervised Learning**:\n   - Regression (e.g., Linear and Logistic Regression).\n   - Classification (e.g., Decision Trees, SVM, KNN).\n   \n2. **Unsupervised Learning**:\n   - Clustering (e.g., K-Means, DBSCAN).\n   - Dimensionality Reduction (e.g., PCA).\n   \n3. **Deep Learning**:\n   - Neural Networks using **Keras** and **TensorFlow**.\n   - Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs).\n   \n4. **Model Optimization**:\n   - Regularization techniques (L1, L2).\n   - Cross-validation, Grid Search, and Random Search for hyperparameter tuning.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsudarshanasrao%2Fee559-machine_learning-usc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsudarshanasrao%2Fee559-machine_learning-usc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsudarshanasrao%2Fee559-machine_learning-usc/lists"}