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  • ๐Ÿ‘‹ Hi, Iโ€™m Dayane Marcos an undergraduate student
  • ๐Ÿ‘€ Iโ€™m interested in machine learning; particularly Graph Neural Networks, Reinforcement Learning and Unsupervised Learning
  • ๐ŸŒฑ Iโ€™m currently learning about Graph Neural Networks and Energy Based Models
  • ๐Ÿ“ซ How to reach me [email protected]

D. Marcos's Projects

auto-gpt icon auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

camel icon camel

๐Ÿซ CAMEL: Communicative Agents for โ€œMindโ€ Exploration of Large Scale Language Model Society

deckard icon deckard

Official implementation of the DECKARD Agent from the paper "Do Embodied Agents Dream of Pixelated Sheep?"

dgl icon dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

dspy icon dspy

DSPy: The framework for programming with foundation models

guidance icon guidance

A guidance language for controlling large language models.

hands-on-llms icon hands-on-llms

๐Ÿฆ– ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป about ๐—Ÿ๐—Ÿ๐— ๐˜€, ๐—Ÿ๐—Ÿ๐— ๐—ข๐—ฝ๐˜€, and ๐˜ƒ๐—ฒ๐—ฐ๐˜๐—ผ๐—ฟ ๐——๐—•๐˜€ for free by designing, training, and deploying a real-time financial advisor LLM system ~ ๐˜ด๐˜ฐ๐˜ถ๐˜ณ๐˜ค๐˜ฆ ๐˜ค๐˜ฐ๐˜ฅ๐˜ฆ + ๐˜ท๐˜ช๐˜ฅ๐˜ฆ๐˜ฐ & ๐˜ณ๐˜ฆ๐˜ข๐˜ฅ๐˜ช๐˜ฏ๐˜จ ๐˜ฎ๐˜ข๐˜ต๐˜ฆ๐˜ณ๐˜ช๐˜ข๐˜ญ๐˜ด

ml-course-notes icon ml-course-notes

๐ŸŽ“ Sharing course notes on all topics related to machine learning, NLP, and AI.

ml-notebooks icon ml-notebooks

:fire: A series of code examples for all sorts of machine learning tasks and applications.

nlp-tutorial icon nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

notebooks icon notebooks

Jupyter notebooks for the Natural Language Processing with Transformers book

personapaper icon personapaper

About This is a repository for sharing papers in the field of persona-based conversational AI. The related source code for each paper is linked if available.

transformers icon transformers

Transformers and related deep network architectures are summarized and implemented here.

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