A curated collection of end-to-end Machine Learning projects — from data preprocessing to model training, evaluation, and deployment. Built by an AI & ML Engineering student from Mumbai, India.
This repository contains my hands-on Machine Learning projects — each one built to solve a real problem, not just follow a tutorial. Every project covers the full ML pipeline:
Data → Preprocessing → Model Training → Evaluation → Deployment
I'm Meet Maru, a CSE (AI & ML) student at VIVA Institute of Technology, Mumbai. These projects represent my growth from understanding ML fundamentals to building production-ready models.
- 🎯 Focus: Supervised learning · Classification · Regression · NLP · Computer Vision
- 🧠 Stack: Python · scikit-learn · Pandas · NumPy · Matplotlib · Flask
- 🔍 Open to: Internships in AI/ML Engineering · Research Collaborations
| Project | Description | Algorithm | Dataset | Status |
|---|---|---|---|---|
| Coming soon | Sentiment Classifier | Naive Bayes / VADER | Custom text data | 🔧 In Progress |
| Coming soon | House Price Predictor | Linear Regression | Kaggle Housing | 🔧 In Progress |
| Coming soon | Spam Email Detector | Logistic Regression | SMS Spam Collection | 🔧 In Progress |
| Coming soon | Image Classifier | CNN / Transfer Learning | CIFAR-10 | 📅 Planned |
Projects are added as they are completed. Star the repo to get notified when new ones drop.
Languages & Libraries
ML_Projects/
├── project-name/
│ ├── data/ # Raw and processed datasets
│ ├── notebooks/ # Jupyter notebooks (EDA + training)
│ ├── model/ # Saved model files (.pkl, .h5)
│ ├── app.py # Flask API (if deployed)
│ ├── requirements.txt
│ └── README.md # Project-specific docs
└── README.md # This file
Each project lives in its own folder with its own README, dataset notes, and model files.
# 1. Clone the repo
git clone https://github.com/ivengexnce/ML_Projects.git
cd ML_Projects
# 2. Navigate to a project
cd project-name
# 3. Install dependencies
pip install -r requirements.txt
# 4. Run the notebook or script
jupyter notebook notebooks/main.ipynb
# or
python app.py- ML Engineering — model deployment, monitoring, and retraining pipelines
- Deep Learning — CNNs, RNNs, and Transformer architectures
- MLOps — Docker + CI/CD for ML models (building on SentiFlow experience)
- LLMs & Prompt Engineering — Llama 2 & 3, RAG pipelines
All levels welcome — beginner to advanced.
# Fork → Branch → Commit → PR
git checkout -b feature/your-project-or-fix
git commit -m "feat: add your ML project"
git push origin feature/your-project-or-fixCheck open issues for ideas. First-time contributors especially welcome — look for good first issue labels.
| Repo | What's inside |
|---|---|
| AI_Projects | Computer vision, NLP, LLM experiments |
| Python_Projects | Automation, GUI tools, beginner-friendly scripts |
| Full_Stack-Projects | Web apps — Flask, HTML/CSS/JS, MySQL |
| SentiFlow | Production sentiment analysis API on AWS |
MIT © Meet Maru — use freely, credit appreciated.
Built by Meet Maru · AI & ML Engineer · Mumbai, India · Open to Internships
Star ⭐ this repo if it helped you — it keeps me motivated to build more.