• Developed robust OCR models using PyTorch, YOLO, and Tesseract for extracting text from complex financial documents.• Integrated machine learning models with a React frontend and FastAPI backend with MongoDB, enabling a user-friendly and scalable solution.• Built predictive sales forecasting models using machine learning techniques in Python.• Employed PyCaret to develop machine learning models for algorithm analysis and recommendation.• Created a user-friendly system with personalized algorithm suggestions based on uploaded datasets.• Integrated the model with a Flask backend and React frontend for a seamless user experience.• Developed a system leveraging Large Language Models (LLMs) and Natural Language Processing (NLP) techniques.• Translated natural language queries into SQL statements, enhancing database communication and querying.• Implemented SQL integration for efficient data retrieval and analysis.• Implemented a Flask backend, React frontend, and PowerBI for data visualization, delivering an end-to- end application.• Leveraged MLflow for effective model tracking, versioning, and deployment.• Utilised Docker for streamlining CI/CD pipelines and Git for version control.