Presentation
Core Capabilities & Expertise:
Conversational AI & LLMs: Designing sophisticated chatbots and AI assistants utilizing LangChain, Retrieval-Augmented Generation (RAG), and advanced APIs.
Highlight: Developed a specialized, context-aware university chatbot leveraging RAG architecture and the Gemini API.
Predictive Analytics & Machine Learning: Engineering custom ML models from the ground up using industry-standard libraries like TensorFlow and Scikit-learn.
Highlight: Built and trained a highly accurate customer churn prediction system to drive data-informed business decisions.
End-to-End Application Development: Bridging the gap between backend AI mechanics and front-end usability by rapidly prototyping and deploying data-driven web applications using Python and Streamlit.
Solid Technical Foundation: Backed by practical internship experience at Unlox and Qspider, active participation in Kaggle, and a deep understanding of core Computer Science principles including Data Structures, DBMS, and PL/SQL.
Why Work With Me?
I do not just train models; I build complete, deployable AI software. Whether you need a custom natural language processing tool, a robust recommendation engine, or an intelligent web application, I deliver clean code and scalable solutions tailored to your specific business needs.
Let’s connect to build intelligent applications that drive real value for your project.
Portfolio
Offered services



Background
* Developed and optimized predictive models (utilizing frameworks like Scikit-learn and TensorFlow) to solve specific business logic problems, strictly monitoring for performance and high accuracy.
* Streamlined model deployment workflows, bridging the gap between raw data analysis and functional AI solutions that can be integrated into broader systems.
* Built automated data systems using Python-based AI frameworks, significantly reducing manual data handling time and improving pipeline efficiency.
* Implemented machine learning algorithms to extract actionable insights from raw data, ensuring all code was clean, scalable, and well-documented for deployment.


