🤖 Artificial Intelligence & Machine Learning Portfolio
Welcome to my AI & Machine Learning portfolio.
Here, I showcase projects where I applied data science, neural networks, deep learning, and MLOps practices to solve real-world problems.
My focus areas include:
- 🧠 Machine Learning → Regression, Classification, Clustering
- 🎨 Computer Vision → Image recognition, Object detection
- 🗣️ Natural Language Processing (NLP) → Text classification, Chatbots
- ☁️ MLOps & Deployment → CI/CD pipelines, Model serving on cloud platforms
🔹 Featured Projects
1. 🏠 Housing Price Prediction (Regression Model)
- Built a regression model to predict housing prices based on location, size, and features
- Used Linear Regression, Random Forest, and Gradient Boosting for comparison
- Integrated a CI/CD pipeline with GitHub Actions for automated training & deployment
👉 View Project
2. 📸 Image Classification with CNN
- Trained a Convolutional Neural Network (CNN) on a custom dataset from Kaggle
- Achieved high accuracy in classifying images into multiple categories
- Deployed model with Flask + AWS EC2 for real-time image classification
👉 View Project
3. 💬 Sentiment Analysis with NLP
- Preprocessed large text datasets for sentiment classification
- Applied TF-IDF, Word2Vec, and LSTMs for feature extraction & modeling
- Built a Streamlit dashboard for interactive text analysis
👉 View Project
4. 🔄 MLOps: End-to-End ML Pipeline
- Automated model training, testing, and deployment with GitHub Actions + Docker
- Integrated with AWS S3, Lambda, and RDS for data handling and deployment
- Showcases scalable machine learning workflows
👉 View Project
🔹 How to Explore
- Each project folder contains:
- 📄 README.md → Detailed explanation of architecture, methods, and results
- 🖼️ Images → System diagrams, model architectures, UI screenshots
- 🎥 Demo links → Video demos or deployed app links
🔹 Next Steps
📂 Browse through my projects, or jump back to my Main Portfolio for Automation, PLC, and Cloud projects.