ML-Learning_Projects

Hands-on Machine Learning Projects for Practice & Portfolio

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🔍 Overview

This public repository contains curated machine learning mini-projects aimed at learning core ML concepts using Python.
Each project is implemented using real-world datasets and popular ML libraries. Ideal for:

• Students & Freshers
• Data Science Enthusiasts
• Interview Preparation
• Portfolio Building

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🧠 Included Projects

🔢 Supervised Learning

Project	Techniques Used
🔹 Linear Regression	Regression, Evaluation Metrics
🔹 Logistic Regression	Binary Classification
🔹 Decision Tree	Tree-based Classification
🔹 Random Forest	Ensemble Methods, Feature Importance
🔹 Support Vector Regression	SVM with kernels
🔹 K-Nearest Neighbors	Lazy Learning, Distance Metrics

🔍 Unsupervised Learning

Project	Techniques Used
🔹 Clustering	K-Means, Elbow Method

📐 Model Validation

Project	Techniques Used
🔹 Cross Validation	K-Fold, Stratified K-Fold, ShuffleSplit

❤️ Applied Projects

Project	Domain
🔹 Heart Disease Prediction	Healthcare AI

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🛠️ Technologies Used

• Python 3.x
• Jupyter Notebook
• scikit-learn, pandas, numpy, matplotlib, seaborn

Tip: These notebooks are best viewed via Jupyter Notebook Viewer or directly on GitHub.

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🚀 Getting Started

🚀 Getting Started

# Clone the repository
git clone https://github.com/VIPULbunny/ML-Learning_Projects.git
cd ML-Learning_Projects

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

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📁 Project Structure

ML-Learning_Projects
├── Clustering
│   ├── Association
│   │     └── Apriori
│   │     └──Eclat
│   └── KMeans
├── Cross Validation Techniques
│   └── Cross_Validation.ipynb
├── Decision Tree
│   └── Car_Price_prediction.ipynb
├── Heart disease Prediction
│   └── Heart_Disease_Prediction.ipynb
├── KNN
│   ├── MOVIES_project
│   └── KNN_Iphone_purchesed.ipynb
├── Linear Regression
│   ├── HousePrice.ipynb
│   └── Linear_Regression_Model.ipynb
├── Logistic Regression
│   ├── Titanic_suvival_project.ipynb
│   └── Logistic_Regression_Model.ipynb
├── Random Forest
│   ├── Credit Card Fraud Detection
│   └── Random_F_Regressor.ipynb
├── Support Vector Regression
│   ├── SVM(SVR)
│   ├── SVM.ipynb
│   ├──SVM_with_STD.ipynb
│   └── SVM_without_STD.ipynb
└── README.md

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🔭 Live Preview Options

• 📘 View on NBViewer
• ⚙️ Run on Google Colab

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👨‍💻 Author

Vipul Solanki
📍 Computer Engineering Student – RGIT, Mumbai
💼 Data Science & AI Enthusiast
📫 Email: vipulsolanki339@gmail.com
🔗 LinkedIn
💻 GitHub

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⭐ Support

If you find this repository helpful:

• ⭐ Star the repo
• 🍴 Fork it
• 🧠 Share it
• 💬 Connect with me

Contributions are welcome!
Feel free to open an issue or submit a pull request.