BCA student building RAG systems, ML models & LangGraph agents.
ML Intern @ Cognifyz Technologies · Python · LangChain · FastAPI · Scikit-learn.
I'm Abhishek Grover, a BCA student at Amity University Online (Semester 5 of 6) based in New Delhi. I'm learning AI and ML engineering by building real projects — RAG pipelines, multi-agent systems, and supervised ML models.
I completed an ML internship at Cognifyz Technologies where I built a restaurant rating prediction model (Gradient Boosting, R²=0.6246 on held-out test data), a weighted content-based recommendation engine, and a geospatial analytics pipeline with 8 visualizations — all on a 9,551-row real-world dataset.
My current focus is on AI Engineering fundamentals: RAG system design with LangChain and ChromaDB, agentic workflows using LangGraph, and production ML pipelines with FastAPI and Docker. My long-term goal is to contribute to production AI systems at scale, targeting roles in AI/ML Engineering.
Machine Learning internship at Cognifyz Technologies. Completed 3 end-to-end ML projects on a real restaurant dataset of 9,551 records — covering supervised regression, content-based recommendation, and geospatial analytics.
Each project included full EDA, preprocessing, model training, evaluation, and a written project report. Source code, Jupyter notebooks, and visualizations are all documented in the repository.
Actively seeking internships and entry-level roles in AI Engineering, ML Engineering, and applied GenAI. If you're building something with RAG, agents, or ML pipelines — I'd be glad to contribute and learn.