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Machine Learning Projects

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+ +[🌐 Live Website](https://shsarv.github.io/Machine-Learning-Projects/)  Β·  [πŸ› Report Bug](https://github.com/shsarv/Machine-Learning-Projects/issues)  Β·  [✨ Request Feature](https://github.com/shsarv/Machine-Learning-Projects/issues) + +
+ +

Project Overview

+

A curated portfolio of 26 end-to-end machine learning projects β€” spanning healthcare AI, real-time computer vision, NLP chatbots, time series forecasting, and classical ML. Each project applies theory to a practical problem, with several fully deployed as web and GUI applications.

+

πŸ“Š Repository at a Glance

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+ +| πŸ“ Projects | 🏷️ Domains | πŸš€ Deployed Apps | πŸ–₯️ GUI Apps | ⭐ GitHub Stars | +|:-----------:|:----------:|:---------------:|:-----------:|:--------------:| +| **26** | **6** | **5** | **3** | **1.3k+** | + +
+ + +## πŸ“š Table of Contents + +
+Click to expand / collapse + +- [πŸ—‚οΈ All Projects by Category](#all-projects-by-category) + - [πŸ₯ Healthcare & Medical AI](#-healthcare--medical-ai) + - [πŸŽ₯ Computer Vision & OpenCV](#-computer-vision--opencv) + - [πŸ“ˆ Classical ML & Prediction](#-classical-ml--prediction) + - [πŸ’¬ NLP & Conversational AI](#-nlp--conversational-ai) + - [πŸ“Š Time Series & Business Analytics](#-time-series--business-analytics) + - [πŸ—ΊοΈ Geospatial & Data Science](#-geospatial-&-data-science) +- [πŸ› οΈ Tech Stack](#-tech-stack) +- [πŸ“ Project Structure](#-project-structure) +- [πŸš€ Getting Started](#-getting-started) +- [🀝 Contribution](#-contributions) +- [πŸ“œ License](#-license) + +
+ +## All Projects by Category + +> **Legend:**   🟒 Beginner   🟑 Intermediate   πŸ”΄ Advanced  |  🌐 Web App   πŸ–₯️ GUI App   πŸ““ Notebook + + +### πŸ₯ Healthcare & Medical AI -![Contributors](https://img.shields.io/github/contributors/shsarv/Machine-Learning-Projects?color=dark-green) -![Forks](https://img.shields.io/github/forks/shsarv/Machine-Learning-Projects?style=social) -![Stargazers](https://img.shields.io/github/stars/shsarv/Machine-Learning-Projects?style=social) -![Issues](https://img.shields.io/github/issues/shsarv/Machine-Learning-Projects) -![License](https://img.shields.io/github/license/shsarv/Machine-Learning-Projects) +
+6 Projects β€” click to collapse + +
+ +| Project | Description | Tools & Algorithms | Level | Type | +|---------|-------------|-------------------|:-----:|:----:| +| [**Brain Tumor Detection**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/BRAIN%20TUMOR%20DETECTION%20%5BEND%202%20END%5D) | Detects tumors in MRI scans using a CNN. Upload a scan and get a real-time prediction. | PyTorch Β· CNN Β· Flask | πŸ”΄ | 🌐 | +| [**Diabetes Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Diabetes%20Prediction%20%5BEND%202%20END%5D) | Predicts diabetes likelihood from 8 health markers (glucose, BMI, insulin, age) using the Pima Indians dataset. | scikit-learn Β· SVM Β· Flask | 🟑 | 🌐 | +| [**Heart Disease Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Heart%20Disease%20Prediction%20%5BEND%202%20END%5D) | Predicts cardiac risk from 13 clinical features with ~92% accuracy. | scikit-learn Β· Logistic Reg. Β· Flask | 🟑 | 🌐 | +| [**Arrhythmia Classification**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Classification%20of%20Arrhythmia%20%5BECG%20DATA%5D) | Classifies 16 arrhythmia types from 279 ECG features (UCI dataset). | SVM Β· KNN Β· Decision Tree | 🟑 | πŸ““ | +| [**Medical Chatbot**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Medical%20Chatbot%20%5BEND%202%20END%5D%20%5BNLP%5D) | NLP chatbot mapping user-described symptoms to diagnoses via a curated medical knowledge base. | NLTK Β· TF-IDF Β· Flask | πŸ”΄ | 🌐 | +| [**MoA Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Mechanisms%20Of%20Action%20(MoA)%20Prediction) | Predicts drug biological activity from gene expression and cell viability data (Kaggle competition). | PyTorch Β· TabNet Β· Multi-label | πŸ”΄ | πŸ““ | + +
+ +------------- + +### πŸŽ₯ Computer Vision & OpenCV + +
+9 Projects β€” click to collapse + +
+ +| Project | Description | Tools & Algorithms | Level | Type | +|---------|-------------|-------------------|:-----:|:----:| +| [**Driver Drowsiness Detection**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Drowsiness%20detection%20%5BOPEN%20CV%5D) | Monitors driver eye state via Eye Aspect Ratio (EAR) and triggers an audio alert on drowsiness. | OpenCV Β· dlib Β· EAR | 🟑 | πŸ–₯️ | +| [**Distracted Driver Detection**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Distracted%20Driver%20Detection) | Classifies 10 distracted behaviors (texting, eating, phone call, etc.) from dashboard camera images. | CNN Β· Keras Β· ImageDataGenerator | πŸ”΄ | πŸ““ | +| [**Lane Line Detection**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Lane%20Line%20Detection%20%5BOPEN%20CV%5D) | Overlays detected road lane lines on images/video using Canny edge detection and Hough transforms. | OpenCV Β· Canny Β· Hough Transform | 🟒 | πŸ–₯️ | +| [**Human Detection & Counting**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Human%20Detection%20%26%20Counting%20Project%20%5BOPEN%20CV%5D) | Detects and counts people in live video or images using HOG + SVM. | OpenCV Β· HOG Β· SVM | 🟒 | πŸ–₯️ | +| [**Gender & Age Detection**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Gender%20and%20age%20detection%20using%20deep%20learning) | Predicts gender and age group from a face image using pre-trained Caffe models. | OpenCV DNN Β· Caffe Models | 🟑 | πŸ–₯️ | +| [**Image Colorization**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Colorize%20Black%20%26%20white%20images%20%5BOPEN%20CV%5D) | Adds realistic color to grayscale photos using the Zhang et al. deep colorization network. | OpenCV DNN Β· Zhang et al. Β· LAB space | 🟑 | πŸ““ | +| [**Smile Selfie Capture**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Smile%20Selfie%20Capture%20%20%5BOPEN%20CV%5D) | Auto-captures a photo the instant a smile is detected in the webcam feed. No button needed. | OpenCV Β· Haar Cascades | 🟒 | πŸ–₯️ | +| [**Emoji Creator from Emotions**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/emoji%20creator%20project%20%5BOPEN%20CV%5D) | Detects real-time facial emotions via webcam and overlays the matching emoji on screen. | OpenCV Β· CNN Β· FER dataset | 🟑 | πŸ–₯️ | +| [**Human Activity Recognition**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Human%20Activity%20Detection) | Classifies activities (walking, sitting, standing) from pose estimation keypoints over time. | LSTM Β· Keras Β· 2D Pose Estimation | πŸ”΄ | πŸ““ | + +
+ +-------- + +### πŸ“ˆ Classical ML & Prediction + +
+7 Projects β€” click to collapse + +
+ +| Project | Description | Tools & Algorithms | Level | Type | +|---------|-------------|-------------------|:-----:|:----:| +| [**Iris Flower Classification**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Iris%20Flower%20Classification) | Classic benchmark β€” classifies iris species from petal/sepal measurements. Ideal for comparing classifiers side-by-side. | KNN Β· SVM Β· Decision Tree Β· Naive Bayes | 🟒 | πŸ““ | +| [**Wine Quality Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Wine%20Quality%20prediction) | Predicts wine quality score (3–8) from 11 physicochemical properties like acidity, sulfates, and alcohol. | Random Forest Β· XGBoost | 🟑 | πŸ““ | +| [**Loan Repayment Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Loan%20Repayment%20Prediction) | Predicts whether a LendingClub borrower will repay based on credit history, income, and loan purpose. | Random Forest Β· XGBoost Β· Class Balancing | 🟑 | πŸ““ | +| [**College Admission Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Getting%20Admission%20in%20College%20Prediction) | Estimates graduate admission probability from GRE, TOEFL, GPA, and research experience. | Linear Reg. Β· Ridge Β· Lasso Β· SVR | 🟒 | πŸ““ | +| [**Employee Turnover Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Predict%20Employee%20Turnover%20with%20scikitlearn) | Identifies employees at high risk of leaving using HR data (satisfaction, evaluations, workload, promotions). | Decision Tree Β· Random Forest | 🟑 | πŸ““ | +| [**Property Maintenance Fines**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Predicting%20Property%20Maintenance%20Fines) | Predicts fine compliance from Detroit's blight dataset β€” a real-world class-imbalance problem (Michigan Data Science Team). | Gradient Boosting Β· SMOTE Β· AUC optimization | πŸ”΄ | πŸ““ | +| [**Research Topic Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Research%20topic%20Prediction) | Classifies academic papers into topic categories using NLP-based feature extraction on titles/abstracts. | TF-IDF Β· Naive Bayes Β· SVM Β· NLTK | 🟑 | πŸ““ | + +
---- -## Project Overview - -Welcome to the **Machine Learning Projects Repository**! This collection encompasses various projects demonstrating core concepts in **machine learning**, **deep learning**, **natural language processing (NLP)**, and **computer vision**. It includes both **deployed applications** (built using **Flask**) and **GUI-based apps** (using **Tkinter**). These projects illustrate the potential of machine learning across domains, including medical diagnosis, human activity recognition, image processing, and more. - -## Project List - -Here’s a detailed list of all projects included in this repository: - -| Project Name | Description | Link | -|---------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------|------| -| **AI Room Booking Chatbot** | An intelligent chatbot built with **IBM Watson Assistant** to facilitate room bookings. | [AI Room Booking Chatbot](https://github.com/shsarv/Machine-Learning-Projects/tree/main/AI%20Room%20Booking%20Chatbot%20%5BIBM%20WATSON%5D) | -| **Brain Tumor Detection (Flask App)** | A deep learning-based **Flask** app for detecting brain tumors in MRI scans using **PyTorch**. Medical professionals can upload scans to receive predictions. | [Brain Tumor Detection](https://github.com/shsarv/Machine-Learning-Projects/tree/main/BRAIN%20TUMOR%20DETECTION%20%5BEND%202%20END%5D) | -| **Arrhythmia Classification** | Predict and classify arrhythmias using **machine learning** algorithms and ECG data. Dataset from the [UCI Repository](https://archive.ics.uci.edu/ml/datasets/Arrhythmia). | [Arrhythmia Classification](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Classification%20of%20Arrhythmia%20%5BECG%20DATA%5D) | -| **Image Colorization** | A deep learning-based solution for colorizing black-and-white images using **OpenCV** and deep neural networks. | [Image Colorization](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Colorize%20Black%20%26%20white%20images%20%5BOPEN%20CV%5D) | -| **Diabetes Prediction (Flask App)** | A web application for predicting the likelihood of diabetes based on health parameters. Built using **Flask** and **scikit-learn**. | [Diabetes Prediction](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Diabetes%20Prediction%20%5BEND%202%20END%5D) | -| **Distracted Driver Detection** | Detect different distracted behaviors of drivers (e.g., texting, eating) using **CNN** and **image classification** techniques. | [Distracted Driver Detection](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Distracted%20Driver%20Detection) | -| **Driver Drowsiness Detection** | Detect drowsiness in drivers using **OpenCV** and **CNN** models based on eye status, with real-time alerts for safety. | [Driver Drowsiness Detection](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Drowsiness%20detection%20%5BOPEN%20CV%5D) | -| **Emoji Generator Based on Emotions (Tkinter)** | A **Tkinter** GUI application that detects facial expressions in real time and generates emojis based on detected emotions. | [Emoji Generator](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Emoji%20Generator) | -| **Gender and Age Detection** | A deep learning-based app that predicts the gender and age of a person using facial images and **OpenCV**. | [Gender and Age Detection](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Gender%20and%20age%20detection%20using%20deep%20learning) | -| **Heart Disease Prediction** | Predict the likelihood of heart disease based on medical attributes. Built using **scikit-learn** models, with 92% accuracy. | [Heart Disease Prediction](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Heart%20Disease%20Prediction%20%5BEND%202%20END%5D) | -| **Human Activity Recognition (LSTM)** | Classify human activities using **2D pose estimation** and **LSTM**. Explore the application of limited dataset inputs for behavior prediction. | [Human Activity Recognition](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Human%20Activity%20Detection) | -| **Human Detection & Counting** | An **OpenCV** project that detects humans in images/videos and counts the number of people present. | [Human Detection & Counting](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Human%20Detection%20%26%20Counting%20Project%20%5BOPEN%20CV%5D) | -| **IPL Score Prediction** | Predict first-inning scores in IPL matches using **EDA** and various regression models (Linear, Decision Tree, Random Forest, etc.). | [IPL Score Prediction](https://github.com/shsarv/Machine-Learning-Projects/tree/main/IPL%20Score%20Prediction) | -| **Iris Flower Classification** | Classify iris flowers into different species based on petal and sepal measurements using classic machine learning algorithms. | [Iris Flower Classification](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Iris%20Flower%20Classification) | -| **Medical Chatbot (NLP)** | A medical chatbot built with **NLP** that uses a dataset of disease symptoms and responds with probable diagnoses. | [Medical Chatbot](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Medical%20Chatbot%20%5BEND%202%20END%5D%20%5BNLP%5D) | -| **Predict Employee Turnover** | Predict employee turnover using **scikit-learn** decision trees and random forest models. | [Predict Employee Turnover](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Predict%20Employee%20Turnover%20with%20scikitlearn) | -| **Wine Quality Prediction** | Predict wine quality using physicochemical features like acidity, sugar, and pH with machine learning models. | [Wine Quality Prediction](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Wine%20Quality%20prediction) | - - -## Technologies Used - -This repository includes a wide range of technologies and tools used in various machine learning and data science projects: - -- **Programming Languages:** Python -- **Libraries/Frameworks:** - - Machine Learning: scikit-learn, TensorFlow, PyTorch, Keras - - NLP: IBM Watson, Natural Language Toolkit (NLTK), SpaCy - - Web Development: Flask - - Image Processing: OpenCV - - GUI Development: Tkinter - - Deep Learning: CNN, LSTM, DNN -- **Tools & Platforms:** - - IBM Watson, Google Colab, Jupyter Notebooks - - Deployed apps using Flask - - Git and GitHub for version control - -## Contributing 🌱 +### πŸ’¬ NLP & Conversational AI -We welcome contributions to this project! If you would like to improve the existing codebase or contribute new features, feel free to submit a pull request. Before submitting, please ensure that you adhere to the following: +
+2 Projects β€” click to collapse -``` -1. **Fork the repository** and create your feature branch: - ```bash - git checkout -b feature/YourFeature - ``` +
-2. **Commit your changes**: - ```bash - git commit -m "Add your feature description" - ``` +| Project | Description | Tools & Algorithms | Level | Type | +|---------|-------------|-------------------|:-----:|:----:| +| [**AI Room Booking Chatbot**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/AI%20Room%20Booking%20Chatbot%20%5BIBM%20WATSON%5D) | Hotel room booking chatbot using IBM Watson. Handles slot-filling, availability queries, and booking confirmations through a web interface. | IBM Watson Assistant Β· Watson Discovery | 🟑 | 🌐 | +| [**Medical Chatbot**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/Medical%20Chatbot%20%5BEND%202%20END%5D%20%5BNLP%5D) | Symptom-to-diagnosis NLP chatbot with multi-turn conversation support. *(Also listed under Healthcare.)* | NLTK Β· Flask Β· TF-IDF Β· Cosine Similarity | πŸ”΄ | 🌐 | -3. **Push your branch** to GitHub: - ```bash - git push origin feature/YourFeature - ``` +
-4. **Open a pull request** to the `main` branch. +----- -For major changes, please open an issue first to discuss what you would like to change. +### πŸ“Š Time Series & Business Analytics ---- +
+2 Projects β€” click to collapse + +
-## πŸ“Š Project Structure +| Project | Description | Tools & Algorithms | Level | Type | +|---------|-------------|-------------------|:-----:|:----:| +| [**Multi-Store Sales Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/TimeSeries%20Multi%20StoreSales%20prediction) | Forecasts daily sales for 50 items across 10 stores using three time series approaches and model ensembling. | ARIMA Β· Facebook Prophet Β· LSTM (Keras) | πŸ”΄ | πŸ““ | +| [**IPL Score Prediction**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/IPL%20Score%20Prediction) | Predicts first-innings T20 scores from ball-by-ball match data with deep EDA and multiple regression models. | Linear/Ridge Reg. Β· Random Forest Β· ANN | 🟑 | πŸ““ | -Each project follows a consistent structure for easy navigation and understanding: -```plaintext +
+ +----- + +### πŸ—ΊοΈ Geospatial & Data Science + +
+1 Project β€” click to collapse + +
+ +| Project | Description | Tools & Algorithms | Level | Type | +|---------|-------------|-------------------|:-----:|:----:| +| [**The Battle of Neighborhoods**](https://github.com/shsarv/Machine-Learning-Projects/tree/main/The%20Battle%20of%20Neighborhoods%20-Coursera%20capstone) | IBM Capstone β€” clusters city neighborhoods using Foursquare API data to recommend optimal business locations. | K-Means Β· Foursquare API Β· Folium Β· Geopy | 🟑 | πŸ““ | + +
+ + +## πŸ› οΈ Tech Stack + +
+ +**Languages & Environments :** ![Python](https://img.shields.io/badge/Python-3776AB?style=flat&logo=python&logoColor=white) +![Jupyter](https://img.shields.io/badge/Jupyter-F37626?style=flat&logo=jupyter&logoColor=white) +![Google Colab](https://img.shields.io/badge/Google%20Colab-F9AB00?style=flat&logo=googlecolab&logoColor=white) + +**Machine Learning & Deep Learning :** ![scikit-learn](https://img.shields.io/badge/scikit--learn-F7931E?style=flat&logo=scikit-learn&logoColor=white) +![TensorFlow](https://img.shields.io/badge/TensorFlow-FF6F00?style=flat&logo=tensorflow&logoColor=white) +![Keras](https://img.shields.io/badge/Keras-D00000?style=flat&logo=keras&logoColor=white) +![PyTorch](https://img.shields.io/badge/PyTorch-EE4C2C?style=flat&logo=pytorch&logoColor=white) +![XGBoost](https://img.shields.io/badge/XGBoost-189FC0?style=flat&logoColor=white) + +**Computer Vision & NLP :** ![OpenCV](https://img.shields.io/badge/OpenCV-5C3EE8?style=flat&logo=opencv&logoColor=white) +![NLTK](https://img.shields.io/badge/NLTK-3F7F4C?style=flat&logoColor=white) +![IBM Watson](https://img.shields.io/badge/IBM%20Watson-BE95FF?style=flat&logo=ibm&logoColor=white) + +**Data & Visualization :** ![Pandas](https://img.shields.io/badge/Pandas-150458?style=flat&logo=pandas&logoColor=white) +![NumPy](https://img.shields.io/badge/NumPy-013243?style=flat&logo=numpy&logoColor=white) +![Matplotlib](https://img.shields.io/badge/Matplotlib-11557C?style=flat&logoColor=white) +![Seaborn](https://img.shields.io/badge/Seaborn-76B900?style=flat&logoColor=white) + +**Deployment :** ![Flask](https://img.shields.io/badge/Flask-000000?style=flat&logo=flask&logoColor=white) +![Heroku](https://img.shields.io/badge/Heroku-430098?style=flat&logo=heroku&logoColor=white) +![Tkinter](https://img.shields.io/badge/Tkinter-GUI-blue?style=flat) + +
+ + +## πŸ“ Project Structure + +Every project follows a consistent layout for easy navigation and reuse: + +``` ProjectName/ β”‚ -β”œβ”€β”€ data/ # Data files and datasets -β”œβ”€β”€ notebooks/ # Jupyter notebooks for experimentation and prototyping -β”œβ”€β”€ models/ # Trained machine learning models (if applicable) -β”œβ”€β”€ static/ # Static files (CSS, JS, images for Flask-based projects) -β”œβ”€β”€ templates/ # HTML templates (for Flask-based projects) -β”œβ”€β”€ src/ # Core Python scripts for data preprocessing, model training, etc. -β”œβ”€β”€ app.py # Main application file for Flask-based projects -β”œβ”€β”€ README.md # Project-specific readme file -└── requirements.txt # List of dependencies for the project +β”œβ”€β”€ πŸ“‚ data/ # Raw and processed datasets +β”œβ”€β”€ πŸ“‚ notebooks/ # Jupyter notebooks (EDA β†’ Training β†’ Evaluation) +β”œβ”€β”€ πŸ“‚ models/ # Saved weights (.pkl / .h5 / .pt) +β”œβ”€β”€ πŸ“‚ static/ # CSS, JS, images (Flask apps) +β”œβ”€β”€ πŸ“‚ templates/ # Jinja2 HTML templates (Flask apps) +β”œβ”€β”€ πŸ“‚ src/ +β”‚ β”œβ”€β”€ preprocess.py # Data cleaning & feature engineering +β”‚ β”œβ”€β”€ train.py # Model training pipeline +β”‚ └── predict.py # Inference logic +β”œβ”€β”€ app.py # Flask entry point (web apps) +β”œβ”€β”€ requirements.txt # Python dependencies +└── README.md # Project-specific documentation ``` -Feel free to explore individual projects to understand the data flow and code structure. - --- -## 🌍 Deployment +## πŸš€ Getting Started + +### Prerequisites + +``` +Python 3.7+ | pip | Git +``` + +### Clone & Run + +```bash +# Clone the repository +git clone https://github.com/shsarv/Machine-Learning-Projects.git +cd Machine-Learning-Projects + +# Navigate to any project +cd "Heart Disease Prediction [END 2 END]" -Some of the projects can be easily deployed on cloud platforms like **Heroku**, **AWS**, or **Azure**. The following steps outline a generic approach for deploying a Flask-based web app on Heroku: +# (Recommended) Create a virtual environment +python -m venv venv +source venv/bin/activate # Linux / macOS +venv\Scripts\activate # Windows -1. **Install Heroku CLI**: - Follow the instructions [here](https://devcenter.heroku.com/articles/heroku-cli). +# Install dependencies +pip install -r requirements.txt -2. **Login to Heroku**: - ```bash - heroku login - ``` +# For Flask web apps +python app.py +# β†’ Open http://127.0.0.1:5000 -3. **Create a new Heroku app**: - ```bash - heroku create your-app-name - ``` +# For notebooks +jupyter notebook +``` + +### Deploy to Heroku + +```bash +heroku login +heroku create your-app-name +echo "web: gunicorn app:app" > Procfile +git push heroku main +heroku open +``` + + + +## Contributions 🌱 + +We welcome contributions to this project! If you would like to improve the existing codebase or contribute new features, feel free to submit a pull request. Before submitting, please ensure that you adhere to the following: -4. **Push to Heroku**: - Ensure your `Procfile` is correctly set up for Flask: - ```plaintext - web: gunicorn app:app - ``` - Then push the project to Heroku: - ```bash - git push heroku main - ``` -5. **View your deployed app**: - ```bash - heroku open - ``` +1. **Fork** this repo +2. **Branch:** `git checkout -b feature/YourProjectName` +3. **Structure** your folder with a `README.md` and `requirements.txt` +4. **Commit:** `git commit -m "Add: YourProjectName"` +5. **Push:** `git push origin feature/YourProjectName` +6. **Open a Pull Request** β†’ target `main` -You can follow similar steps for AWS (using **Elastic Beanstalk**) or Azure (using **App Services**). +Please read [CONTRIBUTING.md](CONTRIBUTING.md) and follow the [Code of Conduct](CODE_OF_CONDUCT.md). -## 🎯 Roadmap -### Future Enhancements: +## Future Enhancements: - [ ] Integrate **Explainable AI (XAI)** models for better understanding of predictions in complex models. - [ ] Add **Docker** support for easy containerization of all projects. - [ ] Incorporate **CI/CD pipelines** using GitHub Actions for automated testing and deployment.