Awesome GenAI
1.0.0
A curated list of resources for generative AI. This includes tutorials, examples, and tools to help you learn and build generative AI models.
| Resource | Description |
|---|---|
| Kaggle Notebooks | ? Kaggle: Access a vast collection of datasets, notebooks, and models. Compete in competitions and collaborate with a community of data scientists to enhance your skills. |
| Hugging Face Spaces | ? Hugging Face Spaces: Discover papers, models, and interactive spaces for natural language processing. Share and deploy your own models with the community. |
| Streamlit Gallery | Streamlit Gallery: Explore a variety of beautiful web apps built with Streamlit. Learn how to create interactive data applications with ease. |
| LangChain Cookbooks | LangChain Cookbook: Find recipes and examples to get started with LangChain. Learn how to build and deploy language models effectively. |
| LangGraph Examples | ? LangGraph Examples: Dive into examples that showcase the capabilities of LangGraph. Understand how to integrate graph-based learning with language models. |
| LangChain How-to Guides | LangChain How-to Guides: Detailed step-by-step guides for using LangChain in various applications. Perfect for beginners and advanced users alike. |
| Pinecone Examples | ? Pinecone Examples: Practical examples demonstrating how to use Pinecone's vector database for building scalable and fast similarity search applications. |
| Trending on GitHub | Trending on GitHub: Stay updated with the most popular repositories in Python and large language model (LLM) topics. Discover new projects and ideas. |
| Future Tools | Future Tools: A comprehensive directory of tools and resources that are shaping the future of AI and technology. Find the latest innovations and trends. |
| There's an AI for That | ? There's an AI for That: An extensive directory of AI tools categorized by their applications. Easily find AI solutions for various tasks. |
| Awesome LLMOps | Awesome LLMOps: A curated list of resources for managing and optimizing large language models. Learn best practices for deployment and maintenance. |
| Best AI Knowledge Repositories | ? Best AI Knowledge Repositories: A collection of the best repositories for AI knowledge and research. Ideal for students and professionals looking to deepen their understanding. |
| Papers with Code | ? Papers with Code: Access state-of-the-art AI research papers with code implementations. Perfect for researchers and practitioners looking to replicate and build upon cutting-edge work. |
| Awesome LangChain | ? Awesome LangChain: A curated list of resources, tools, and tutorials for LangChain. Stay up-to-date with the latest developments and community projects. |
| Awesome Python Data Science | Awesome Python Data Science: A curated list of Python libraries and resources for data science. Enhance your data analysis and machine learning skills. |
| LLM Course | ? LLM Course: Comprehensive course materials for learning about large language models. Includes lectures, assignments, and project ideas. |
| LLMs from Scratch | LLMs from Scratch: Learn how to build large language models from scratch. Understand the fundamentals and implementation details. |
| ZenML Projects | ? ZenML Projects: Example projects using ZenML to streamline your machine learning workflows. Learn how to integrate ZenML into your ML pipelines. |
| Ashish Patel's Projects | Ashish Patel's Projects: Explore a wide range of AI and ML projects listed by Ashish Patel. Includes projects on machine learning, deep learning, computer vision, and NLP with code. |
| LlamaIndex Examples | ? LlamaIndex Examples: Examples demonstrating how to use LlamaIndex for efficient information retrieval and indexing. |
| CrewAI Examples | CrewAI Examples: Practical examples for using CrewAI to enhance team collaboration and productivity in AI projects. |
| JY Chia's Blog | ✍️ JY Chia's Blog: Insightful blog posts about AI, machine learning, and data science. Gain practical tips and knowledge from an experienced professional. |
| DataCamp Cheat Sheets | ? DataCamp Cheat Sheets: Handy cheat sheets for data science and AI concepts. Perfect for quick reference and revision. |
| Qdrant Documentation Examples | Qdrant Documentation Examples: Examples for using Qdrant's vector search capabilities. Learn how to build and deploy vector search applications. |
| MLflow Examples | ? MLflow Examples: Practical examples for using MLflow to manage your machine learning experiments. |
| Comet Examples | ☄️ Comet Examples: Examples for using Comet to track, compare, and optimize your machine learning experiments. |
| W&B Examples | ?️ Weights & Biases Examples: Examples for using Weights & Biases to enhance your ML experiments with tracking, visualization, and collaboration tools. |
| Prefect Recipes | ? Prefect Recipes: Recipes and examples for using Prefect to orchestrate and manage your data workflows. |
| Pachyderm Examples | ? Pachyderm Examples: Examples for using Pachyderm to version and manage your data science pipelines. |
| Amazon SageMaker Examples | ☁️ Amazon SageMaker Examples: Practical examples for using Amazon SageMaker to build, train, and deploy machine learning models at scale. |
| Microsoft Autogen Notebooks | ? Microsoft Autogen Notebooks: Notebooks for using Microsoft Autogen to automate the generation of synthetic data and models. |
| Haystack Tutorials | ? Haystack Tutorials: Tutorials for using Haystack to build powerful search systems with state-of-the-art NLP. |
| Generative AI for Beginners | ? Generative AI for Beginners: A beginner's guide to understanding and building generative AI models. |
| Prompting Guide | Prompting Guide: A comprehensive guide for crafting effective prompts to improve the performance of your AI models. |
| NVIDIA NeMo Examples | NVIDIA NeMo Examples: Examples for using NVIDIA NeMo to build, train, and deploy conversational AI models. |
| Outlines Examples | ✏️ Outlines Examples: Examples for using Outlines to create structured data extraction workflows. |
| Google Cloud Generative AI | ☁️ Google Cloud Generative AI: Resources and examples for building generative AI models on Google Cloud. |
| Hugging Face Transformers Examples | Hugging Face Transformers Examples: Examples for using Hugging Face Transformers to implement state-of-the-art NLP models. |
| e2b Cookbook | e2b Cookbook: Examples and recipes from the e2b cookbook to help you get started with various AI and ML tasks. |
| Google Colab Notebooks | Google Colab Notebooks: Create and share Jupyter notebooks with free access to GPUs. Perfect for experimenting with AI models and collaborating with others. |
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