A curated collection of machine learning projects exploring classification, regression, model evaluation, and data analysis. Each project is self‑contained in its own folder with code, datasets (or links), and documentation.
- Amazon Alexa Reviews – Sentiment classification of customer reviews.
- Mobile Price Range Classification – Predicting mobile price categories.
- College Performance Analysis – Exploratory data analysis of college datasets.
- Auto MPG EDA – Exploratory data analysis and model selection for MPG prediction.
- Stock Price Prediction – Time series forecasting of stock prices.
- Car Sales Prediction – Linear regression with evaluation metrics.
- Credit Card Default Classification – Naive Bayes on an imbalanced dataset.
- Diabetes Prediction – Cross‑validation techniques for medical classification.
- Model Benchmark – Comparing classification models across datasets.
- Handwritten Digits Classification – SVM with hyperparameter tuning via Grid Search.
- Play Tennis Classification – Decision Trees with ID3, CART, and bagging ensembles.
- Python 3.8+
- scikit‑learn, pandas, numpy, matplotlib, seaborn
- Jupyter Notebooks
Clone the repository and explore any project folder:
git clone https://github.com/HariniS1018/machine-learning-projects.git
cd machine-learning-projects/<project-folder>Each folder contains its own notebook to run.
✨ This repo serves as a learning portfolio, showcasing different ML techniques and their applications.