Welcome to my portfolio! This repository showcases my projects, skills, and experience as a Machine Learning Engineer and Data Scientist.
Hi, my name is Nimit Dave. I am a Machine Learning Engineer and Data Scientist with a passion for developing innovative AI solutions. This portfolio highlights some of the projects I have worked on, showcasing my expertise in machine learning, data analytics, and software development.
FitFusion AI is a personalized fitness and nutrition coach application developed using advanced technologies such as LangChain, OpenAI API, FastAPI, and React.js. The project involved creating a multi-agent system that handles user interactions, retrieves data from external APIs, and generates dynamic workout and meal plans using deep learning models. By leveraging Docker and Kubernetes, the application ensures scalability and reliability. The platform has successfully enhanced user engagement by providing customized fitness routines and meal plans, leading to better adherence to fitness goals and measurable health improvements.
The AI-Driven Job Application System is a robust multi-agent platform designed to improve job application processes using LangGraph and LangChain technologies. The system implements machine learning and Retrieval-Augmented Generation (RAG) to increase ATS pass-through rates by 30%. It generates customized cover letters tailored to specific job descriptions, improving their relevance by 25%. The project was developed using Agile methodologies, which reduced development time by 20% and enhanced overall performance, providing a significant boost to job seekers' application success rates.
Amazon Review Analytics is an innovative NLP-based system designed to analyze and perform semantic searches on Amazon product reviews. The project utilized fine-tuning of the BERT model and Transfer Learning on GCP with TensorFlow and Keras, resulting in a 20% increase in prediction accuracy. The system's reliability and deployment were enhanced using Docker, Kubernetes, and Terraform. Additionally, data ingestion and pipeline engineering with Apache Spark automated CI/CD/CM/CT processes, accelerating updates by 40%. This project demonstrated significant improvements in understanding customer sentiments and extracting valuable insights from vast amounts of review data.
- Programming Languages: Python, C/C++, SQL, JavaScript, HTML/CSS
- Machine Learning and AI: TensorFlow, PyTorch, Scikit-Learn, Keras, Hugging Face Transformers, LangChain, LangGraph, OpenCV, Computer Vision, Multi-Modal AI, NLP, Reinforcement Learning, Supervised and Unsupervised Learning
- Data Engineering and Big Data: Apache Airflow, Apache Spark, Kubernetes, Docker, MLflow, FastAPI, AWS, GCP, Terraform, Snowflake
- Data Visualization: Power BI, Tableau, Matplotlib, Seaborn
- Web Development and Frameworks: React, Node.js, Flask, FastAPI
- Development Tools and Practices: Git, VS Code, Pycharm, Jira, CI/CD, Agile Methodologies
- Databases and Data Storage: SQL, Elasticsearch, Kibana
- Other Relevant Tools and Libraries: NumPy, Pandas, Streamlit, Heroku