Democratizing Artificial Intelligence Research, Education, and Technologies
69
Repositórios públicos
157.411
Total de estrelas
9.499
Seguidores
A organização DAIR.AI no GitHub se dedica à pesquisa e educação em inteligência artificial, apresentando uma ampla gama de repositórios públicos. Utilizando linguagens como Jupyter Notebook, Python e TypeScript, seus projetos notáveis incluem o Prompt-Engineering-Guide e ml-visuals, que oferecem recursos valiosos para a comunidade.
Principais linguagens
Repositórios públicos
Prompt-Engineering-Guide
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
ML-YouTube-Courses
📺 Discover the latest machine learning / AI courses on YouTube.
AI-Papers-of-the-Week
🔥Highlighting the top ML papers every week.
ML-Papers-Explained
Explanation to key concepts in ML
ML-Course-Notes
🎓 Sharing machine learning course / lecture notes.
Mathematics-for-ML
🧮 A collection of resources to learn mathematics for machine learning
ML-Notebooks
:fire: Machine Learning Notebooks
Transformers-Recipe
🧠 A study guide to learn about Transformers
nlp_paper_summaries
✍️ A carefully curated list of NLP paper summaries
GNNs-Recipe
🟠 A study guide to learn about Graph Neural Networks (GNNs)
MLOPs-Primer
A collection of resources to learn about MLOPs.
AI-Product-Index
A curated index to track AI-powered products.
pytorch_notebooks
🔥 A collection of PyTorch notebooks for learning and practicing deep learning
d2l-study-group
🧠 Material for the Deep Learning Study Group
nlp_fundamentals
📘 Contains a series of hands-on notebooks for learning the fundamentals of NLP
nlp_newsletter
📰Natural language processing (NLP) newsletter
dair-academy-plugins
DAIR.AI Academy Plugins
awesome-ML-projects-guide
A guide to building awesome machine learning projects.
dair-ai.github.io
Home of DAIR.AI
emotion_dataset
:smile: Dataset for Emotion Recognition Research
m2-deep-research
Deep research agents using MiniMax M2.1 interleaved thinking
awesome-research-proposals-guide
A guide to improve your research proposals.
ml-nlp-paper-discussions
📄 A repo containing notes and discussions for our weekly NLP/ML paper discussions.
keep-learning-ml
A club to keep learning about ML
dair-workshops
Nenhuma descrição fornecida para este repositório.
nlp_overview
📘Overview of Modern Deep Learning Techniques Applied to Natural Language Processing
notebooks
🔬 Sharing your data science notebooks with the community has never been this easy.
deep-ai-research
Claude agent for Deep AI Research
covid_19_search_application
Text Similarity Search Application using Modern NLP and Elasticsearch
maven-pe-for-llms-4
Prompt Engineering for Large Language Models - Notebooks, Demos, Exercises, and Projects
odsc_2020_nlp
Repository for ODSC talk related to Deep Learning NLP
deep-research-n8n
Deploy a mult-agent deep research agent with Replit and n8n
research_emotion_analysis
:smile: Multilingual emotion analysis research
llm-evaluator
Example for Logging LLM Evaluator Prompt Responses
data_science_writing_primer
Writing Primer for Data Scientists
nlp_highlights
✨ A report of the most important NLP highlights (A Yearly Report - 2018, 2019)
pe-for-llms
Nenhuma descrição fornecida para este repositório.
datasets
AI Datasets
maven-pe-for-llms
Nenhuma descrição fornecida para este repositório.
paper_implementations
A project for implementing ML and NLP papers
cursor-course
Nenhuma descrição fornecida para este repositório.
deep_learning_notations
➕Contains useful deep learning notations for writing blogs, presentations, and papers.
maven-pe-for-llms-6
Materials for the Prompt Engineering for LLMs (Cohort 6)
cursor-final-project
Final project for the Cursor course
maven-pe-for-llms-8
Materials for the Prompt Engineering for LLMs (Cohort 8)
nlp_with_tensorflow
NLP tutorials I have written using TensorFlow
maven-pe-for-llms-12
Course material for Prompt Engineering for LLMs
maven-pe-for-llms-11
Materials for the Prompt Engineering for LLMs Course (Cohort 11)
maven-pe-for-llms-13
Materials for the Prompt Engineering for LLMs (Cohort 13)
maven-pe-for-llms-9
Materials for Prompt Engineering for LLMs (Cohort 9)
maven-pe-for-llms-7
Code, Demos, and Exercises for Prompt Engineering for LLMs Course
deep-research-agent
Nenhuma descrição fornecida para este repositório.
cc-cohort-3
Nenhuma descrição fornecida para este repositório.
comet-llm
comet llm support
deep_affective_layer
:smile: Building a deep learning based affective computing platform
paper_presentations
All paper presentation material will be added here
mri-analysis-pytorch
🧠MRI analysis using PyTorch and MedicalTorch
deep-research-initial-project
Nenhuma descrição fornecida para este repositório.
.github
Nenhuma descrição fornecida para este repositório.
maven-pe-for-llms-10
Materials for Cohort 10
maven-pe-for-llms-2
Nenhuma descrição fornecida para este repositório.
dair-cc-plugins
DAIR.AI Claude Code Plugins
text-embeddings
Nenhuma descrição fornecida para este repositório.
appworks_meetup_2018
Contains all the material used for the "Applied Deep Learning for NLP Using PyTorch" meetup at AppWorks
wiki-sft
Nenhuma descrição fornecida para este repositório.
dr-agent
Nenhuma descrição fornecida para este repositório.
claude-code-course-c1
Nenhuma descrição fornecida para este repositório.
helsinki_ml
Machine Learning in the Elastic Stack
Perguntas frequentes
O que a dair-ai desenvolve no GitHub?
A dair-ai desenvolve uma variedade de repositórios focados em inteligência artificial e aprendizado de máquina. Seus projetos incluem guias, visuais para escrita científica e listas de cursos de IA, visando democratizar o acesso ao conhecimento na área.
Quais linguagens de programação a dair-ai utiliza?
A dair-ai utiliza principalmente Jupyter Notebook, Python e TypeScript, além de HTML, MDX e CSS. Essas linguagens suportam uma diversidade de projetos voltados à pesquisa e educação em inteligência artificial.
Os repositórios da dair-ai são públicos?
Sim, todos os repositórios da dair-ai são públicos. Isso permite que a comunidade acesse, utilize e colabore em projetos relacionados à inteligência artificial, promovendo um ambiente de aprendizado compartilhado.
Essa exposição é intencional?
Monitore DAIR.AI com o RepoGuard e receba alertas no momento em que um novo repositório público aparecer.
Monitore esta conta