Welcome to my GitHub profile!
- 🔭 I’m currently pursuing MS in Data Science at University of Massachusetts Dartmouth.
- 🌱 I'm currently learning advanced Deep Learning architectures and mastering MLOps with cloud platforms like Azure ML and AWS, along with Generative AI, Language Models, and Large Language Models (LLMs).
- 🎓 I’m a Microsoft Certified: Azure Data Scientist Associate
- 📫 How to reach me: LinkedIn
- 😄 Pronouns: She/Her
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PyTorch with PyTorch Lightning
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Basic PyTorch
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Docker & CI/CD
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Experiment Tracking & Model Management
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Object Detection
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Image Classification
- Transformers & LLMs
- Data Structures & Algorithms
| Project | Description | Tech Stack |
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| Hyperparameter Tuning and Optimization with Experiment Tracking | This project explores Hyperparameter Optimization for a deep learning Classification model. It highlights streamlined workflows for experiment tracking, model tuning, and reporting with ML tools. |
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| Deep Learning Classification with PyTorch Lightning and Hydra Integration | This project implements a state-of-the-art dog breed classification model using PyTorch Lightning and Hydra. It's designed to accurately identify dog breeds from images, utilizing deep learning. |
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| Deep Learning Classification - Training & Inference with PyTorch Lightning | This project demonstrates how to set up training, evaluation, and inference for dog breed classification using Docker and PyTorch Lightning. |
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| MNIST Classification - Dockerized Training Evaluation Inference with PyTorch | This project offers a Docker Compose setup for managing training, evaluation, and inference on both the MNIST Hogwild dataset using PyTorch. |
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| Dockerized Training for MNIST Digit Classification with PyTorch | This project trains a Convolution Neural Network (CNN) for MNIST dataset digit classification using PyTorch, fully containerized with Docker. It supports training from scratch, resuming from checkpoints, and evaluation. |
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