Shaik Shaheer

• Sentiment Analysis on Product Reviews with MLflow Integration and Prefect Workflow • Implemented advanced data preprocessing techniques for training machine learning models, utilizing F1-Score for sentiment classification evaluation, alongside MLflow for model registration and management, and integrated Prefect Workflow for automated scheduling and execution of sentiment analysis tasks. • Deployed the trained sentiment classification model integrated with a Flask web application on an AWS EC2 instance, enabling real-time inference and user interaction. • AI Code Reviewer App • Led the development of Generative AI App - AI Code Reviewer, a Python application offering comprehensive feedback on code submissions, featuring a user-friendly interface built with Streamlit for seamless interaction. Engineered an efficient system utilizing the OpenAI API for advanced code review, enabling automated analysis of code for bugs and errors. • System on “Leave No Context Behind” Paper using LangChain • Created a RAG (Retrieval-Augmented Generation) system leveraging the LangChain framework, integrating Gemini 1.5 Pro LLM capabilities with external data for enhanced information retrieval and generation, and connecting LLMs with company-specific data from PDFs and text files for improved applications and user experiences.