Extensive experience with most core machine learning algorithms — classification, regression, and clustering — using tools like Scikit-learn to solve real-world problems.

Cleaning, transforming, and engineering features with Pandas and NumPy for robust, high-quality machine learning pipelines.

Building CNNs and applying transfer learning for tasks like image classification and medical imaging with PyTorch and TensorFlow.

Creating impactful plots using Matplotlib, Seaborn, and Plotly to communicate insights and uncover hidden trends.

Working with large language models (LLMs) and modern NLP techniques to build smart assistants, chatbots, and text understanding systems using tools like Ollama, LLaMA, and OpenWebUI.

Deploying ML models using FastAPI, Docker, and CI/CD tools to build scalable, production-ready solutions.

Automating data extraction using BeautifulSoup, Selenium, and Requests to collect structured datasets from the web.

Building RESTful APIs and lightweight web backends using FastAPI, Flask, and Node.js — enabling seamless integration of ML models and automation pipelines.

Developing full-stack applications using React, TypeScript, Tailwind CSS, Node.js, and MongoDB — delivering clean UIs and performant backends with modern tooling.