Skip to content
View Melody-coder923's full-sized avatar
💭
study 🧑‍🎓
💭
study 🧑‍🎓
  • Northeastern University
  • Seattle
  • 09:42 (UTC -07:00)

Highlights

  • Pro

Block or report Melody-coder923

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 250 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Melody-coder923/README.md

Hey there! I'm Melody

About me:

  • Currently pursuing a Master's degree in Software Engineering at Northeastern University.
  • I'm on track for learning more about Artificial Intelligence, Systems Design, and Cloud Architecture.
  • How to reach me: [email protected]
  • Fun fact: I've visited more than 56 countries.

Interests

  • AI Software Development
  • Machine Learning

Blogs

Software & AI Projects | Open Source Contributions

  • Built AI-agent travel chatbot with Agno, Groq, and ChromaDB; fine-tuned model weights and open-sourced them.
  • Open source contributor to notable open-source projects including:
    • HuggingFace Transformers
    • LangChain
    • JAX
  • Studied the foundational paper "ZeRo" and implemented a DeepSpeed + PyTorch project for efficient distributed training and evaluation, optimizing resource usage and training speed for large-scale deep learning tasks.
  • Implemented data parallelism for MNIST training with JAX's shardmap sharding API and contributed to OSS JAX.
  • Built and extended Micrograd, a minimal autograd engine, as part of self-study of Karpathy's Zero to Hero series:
    • Implemented the Value class, topological sort–based backpropagation, and dynamically constructed computation graph (DAG).
    • Added custom operations (e.g., exponentiation, ReLU, tanh), visualized graph structures, and built training loop for an MLP.
    • Reinforced understanding of the chain rule, gradient descent, and autograd principles through end-to-end implementation.

Projects:

  • AI project to plan travel itineraries.
  • Built with Python and machine learning to provide personalized travel recommendations.
  • Neural network implementation in Python.
  • Focuses on understanding how neural networks work by implementing backpropagation from scratch.
  • Learning by building. Learn by sharing.
  • This repository contains weekly solutions to Data Structures and Algorithms (DSA) challenges.
  • The model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models for both inference and training.
  • Contributed to the open-source community by improving the usability and performance of this powerful library.
  • Python, PyTorch, TensorFlow
  • Digital marketing project based on the Solar Sisters initiative to promote sustainable energy solutions.
  • Python, Data Analysis, Marketing
  • Large-scale deep learning model training and evaluation with DeepSpeed and PyTorch.
  • DeepSpeed, PyTorch, Machine Learning
  • The model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models for both inference and training.
  • Contributed to the open-source community by improving the usability and performance of this powerful library.
  • Python, PyTorch, TensorFlow

Pinned Loading

  1. Travel-Agent-App Travel-Agent-App Public

    Python

  2. micrograd micrograd Public

    Jupyter Notebook

  3. Weekly-DSA-Journey Weekly-DSA-Journey Public

    Learning by building. Learn by sharing. 👨‍💻✨

  4. huggingface/transformers huggingface/transformers Public

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

    Python 150k 30.5k