In my relatively short career, I've actively contributed to a range of projects, emphasizing my expertise in both backend development and artificial intelligence (AI). Engaging with frameworks like FastAPI and Django, I've crafted robust backend solutions, ensuring optimal performance and reliability. Simultaneously, I've delved into AI projects, leveraging various libraries to implement advanced algorithms and models. Here are some of those.

1. Digital Twin

Led the development of a high-performance FastAPI backend from inception, addressing performance challenges experienced with Anvil. Integrated Databricks, AWS S3, and AWS EC2 to create a robust data processing pipeline using PySpark for efficient handling of large datasets. Implemented APIs for training machine learning models with PyTorch on Databricks.

2. Know Your Data

Created a web application using streamlit to get the best-performing model on data provided by users. Users can visualize data, apply preprocessing on data, and find a perfect model for predicting new outputs.

3. Q&A Using Langchain and Openai

Developed a compact yet impactful project integrating LangChain, OpenAI, and Pinecone to facilitate efficient information retrieval from PDF-formatted books. Leveraging the power of LangChain for language processing, OpenAI for advanced natural language understanding, and Pinecone for robust search capabilities, the project enables users to effortlessly extract answers from any book in PDF format. This innovative solution streamlines the process of accessing relevant information, showcasing the seamless integration of cutting-edge technologies to enhance the user experience in navigating extensive written content.