I am a passionate AI & Machine Learning Engineer with hands-on experience in building end-to-end ML systems, from data pipelines and model training to production-grade deployment on cloud platforms.

I focus on real-world problem solving, combining Machine Learning, Computer Vision, Backend Development, Docker, and Cloud (AWS) to build scalable and practical applications.

• Languages: Python, SQL, HTML/CSS
• Machine Learning: Scikit-learn, Pandas, NumPy, Model Evaluation, Feature Engineering
• Computer Vision: Object Detection, OpenCV, Real-time Inference
• Backend & APIs: Flask, FastAPI
• DevOps & Cloud: Docker, AWS Elastic Beanstalk
• Tools: Git, GitHub, VS Code

📌 Built a production-ready ML system to predict student academic performance and classify academic risk levels (Low / Medium / High) for early intervention.

Key Highlights:

• End-to-end ML pipeline (data ingestion → transformation → training → inference)
• Flask-based web application with clean UI
• Dockerized for consistent deployment
• Deployed on AWS Elastic Beanstalk (Free Tier)
• Real-world decision-focused output (risk categorization)

🌐 Live Demo (AWS): http://student-performance-env.eba-cvqd8nbt.us-west-2.elasticbeanstalk.com/

📌 Developed a Computer Vision-based Advanced Driver Assistance System (ADAS) capable of real-time object detection and collision avoidance logic, inspired by autonomous driving systems.

Key Highlights:

• Real-time object detection using computer vision techniques
• Distance-based collision warning logic
• Practical application in autonomous vehicles and safety systems
• Strong focus on real-world constraints and decision making

🔗 GitHub: https://github.com/ishaannk/ADAS-Object-Detection-and-Collision-Avoidance

📧 Email: iamishank97@gmail.com
🔗 GitHub: https://github.com/ishaannk

⭐ If you find my work interesting, feel free to ⭐ my repositories!