🎯 AI ML ENGINEER | 📍 Pune, Maharashtra, India
🧠 Passionate about solving real-world problems with data and AI.
🌱 A curious and self-driven learner, always exploring new tools and technologies to grow every day
- 📊 Strong foundation in Statistics, Machine Learning, and Deep Learning
- 🤖 Currently diving deeper into Generative AI and advanced NLP techniques
- 🛠️ Hands-on experience building end-to-end solutions:
- 📌 Project experience in Computer Vision, Time Series Analysis, and LLM-powered apps
- 🌍 Sharing knowledge through blogs and contributing to open-source communities
- 🚀 Passionate about building intelligent, scalable, and impactful AI solutions that bridge the gap between research and real-world implementation
Programming & Query Languages: Python, SQL
Machine Learning & Deep Learning: Supervised & Unsupervised Learning, Computer Vision, CNN, RNN, LSTM, Feature Engineering
Gen AI & LLMs: LangChain, Hugging Face Transformers, RAG, Prompt Engineering, Gemini, OpenAI GPT
Natural Language Processing (NLP): Sentiment Analysis, Document Question Answering, , TF-IDF, Word2Vec
Libraries & Frameworks: Opencv-python, Scikit-learn, TensorFlow, Keras, Pandas, NumPy, Matplotlib, Seaborn
Vector Databases & Big Data Tools: FAISS, PySpark
Deployment & Web Technologies: Streamlit, Flask, Jinja Templating, AWS
Tools & Platforms: Jupyter Notebook, Google Colab, Git, Power BI, VS Code
Soft Skills: Problem Solving, Critical Thinking, Collaboration, Communication, Adaptability
- Advanced Data Science with Python — NASSCOM FutureSkills Prime (April 2025)
Here are some of the projects I’ve worked on:
🔍 Sentiment Analysis of Flipkart Product Reviews
Built an end-to-end sentiment analysis pipeline with real-time deployment using TF-IDF, Word2Vec, and BERT embeddings.🏡 House Price Prediction – King City
Regression project using multiple algorithms including XGBoost (R² = 0.89).🍄 Mushroom Classification
Classifier to determine edibility of mushrooms with 95% accuracy using Random Forest.
You can find more of my work in the Repositories section.
“Data is the new oil, but it’s only valuable when refined — let's refine it together!”