https://github.com/pavans01/ml-hw
Machine Learning Course Assignments
https://github.com/pavans01/ml-hw
Last synced: 25 days ago
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Machine Learning Course Assignments
- Host: GitHub
- URL: https://github.com/pavans01/ml-hw
- Owner: PavanS01
- Created: 2024-05-13T17:36:46.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-13T18:14:19.000Z (about 2 years ago)
- Last Synced: 2025-02-21T22:42:40.978Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 1.4 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Machine Learning Course Projects
Welcome to the repository for projects completed as part of my Machine Learning course. Here's a brief overview of each project:
## 1st Project - Linear and Logistic Regression
Implemented a linear regression model from scratch with 5-fold cross-validation to compute RMSE for each validation set across 5 folds. Additionally, built a logistic regression model and generated ROC curves for each fold, computing the area under the curve.
## 2nd Project - Classification Tree and XGBoost
Implemented a classification tree from scratch for prediction tasks. Also, trained an XGBoost model with L2 regularization to enhance prediction accuracy.
## 3rd Project - Support Vector Machines (SVM)
Explored the capabilities of Support Vector Machines (SVM) by implementing four different models with various kernels:
1. Linear kernel
2. RBF kernel
3. Polynomial (degree 3) kernel
## 4th Project - Convolutional Neural Network (CNN)
Implemented a Convolutional Neural Network (CNN) using PyTorch to classify digits in the MNIST dataset, demonstrating proficiency in deep learning techniques.
Each project folder contains detailed documentation and code to understand the implementation and results thoroughly.
Feel free to explore the respective directories for more information on each project. If you have any questions or suggestions, don't hesitate to reach out. Happy exploring!