Mohammad yaseer Shaik

I've developed Python full-stack and database-driven applications through my trainee role at Codegnan IT Solutions and academic projects.

For an AI Image Library semantic search platform, I designed a six-table PostgreSQL schema, built the SQLAlchemy data layer, managed migrations with Alembic, and integrated Pinecone for CLIP-generated image embeddings. I collaborated with FastAPI, AI pipeline, and React developers to align database contracts with REST API design.

I also built a Flask and Gradio book recommendation application using Neural Collaborative Filtering with TensorFlow and Keras. It achieved 90.2% Precision@10, a 0.013 mean squared error, and API response times under 2.4 seconds for up to 1,000 concurrent users.

I'm focused on applying Python, Flask, MySQL, PostgreSQL, HTML, CSS, and JavaScript to build efficient, scalable, user-friendly web applications while continuing to learn industry practices and emerging technologies.