How to: Jupyter Notebook
- [allenai/OLMoE](https://github.com/allenai/OLMoE) - OLMoE: Open Mixture-of-Experts Language Models
- [hesamsheikh/ml-retreat](https://github.com/hesamsheikh/ml-retreat) - Machine Learning Journal for Intermediate to Advanced Topics.
- [microsoft/AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners) - 12 Weeks, 24 Lessons, AI for All!
- [QwenLM/Qwen2.5-Omni](https://github.com/QwenLM/Qwen2.5-Omni) - Qwen2.5-Omni is an end-to-end multimodal model by Qwen team at Alibaba Cloud, capable of understanding text, audio, vision, video, and performing real-time speech generation.
- [adrida/tarmac](https://github.com/adrida/tarmac) - Explainable git diff for your ML models
- [AnswerDotAI/llms-txt](https://github.com/AnswerDotAI/llms-txt) - The /llms.txt file, helping language models use your website
- [unslothai/notebooks](https://github.com/unslothai/notebooks) - 100+ Fine-tuning Tutorial Notebooks on Google Colab, Kaggle and more.
- [google-gemini/gemini-fullstack-langgraph-quickstart](https://github.com/google-gemini/gemini-fullstack-langgraph-quickstart) - Get started with building Fullstack Agents using Gemini 2.5 and LangGraph
- [google-gemini/cookbook](https://github.com/google-gemini/cookbook) - Examples and guides for using the Gemini API
- [huggingface/optimum-intel](https://github.com/huggingface/optimum-intel) - 🤗 Optimum Intel: Accelerate inference with Intel optimization tools
- [huggingface/smol-course](https://github.com/huggingface/smol-course) - A course on aligning smol models.
- [GoogleCloudPlatform/generative-ai](https://github.com/GoogleCloudPlatform/generative-ai) - Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
- [XiongjieDai/GPU-Benchmarks-on-LLM-Inference](https://github.com/XiongjieDai/GPU-Benchmarks-on-LLM-Inference) - Multiple NVIDIA GPUs or Apple Silicon for Large Language Model Inference?
- [meta-llama/llama-cookbook](https://github.com/meta-llama/llama-cookbook) - Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model f
- [QwenLM/Qwen3-VL](https://github.com/QwenLM/Qwen3-VL) - Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.
- [bellingcat/smart-image-sorter](https://github.com/bellingcat/smart-image-sorter) - User friendly zero-shot image classification using open-source models from the Hugging Face library
- [google-gemini/gemma-cookbook](https://github.com/google-gemini/gemma-cookbook) - A collection of guides and examples for the Gemma open models from Google.
- [microsoft/generative-ai-for-beginners](https://github.com/microsoft/generative-ai-for-beginners) - 21 Lessons, Get Started Building with Generative AI
- [rasbt/LLMs-from-scratch](https://github.com/rasbt/LLMs-from-scratch) - Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
- [bofenghuang/vigogne](https://github.com/bofenghuang/vigogne) - French instruction-following and chat models
- [mistralai/mistral-inference](https://github.com/mistralai/mistral-inference) - Official inference library for Mistral models
- [facebookresearch/audiocraft](https://github.com/facebookresearch/audiocraft) - Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable mu
- [stefan-jansen/machine-learning-for-trading](https://github.com/stefan-jansen/machine-learning-for-trading) - Code for Machine Learning for Algorithmic Trading, 2nd edition.
- [alphacep/vosk-api](https://github.com/alphacep/vosk-api) - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
- [burstable-ai/burst](https://github.com/burstable-ai/burst) - Command-line tool to remotely execute code in the cloud
- [etalab/calculette-impots-m-language-parser](https://github.com/etalab/calculette-impots-m-language-parser) - Calculette de l'impôt sur le revenu parsée
- [unsplash/datasets](https://github.com/unsplash/datasets) - 🎁  6,500,000+ Unsplash images made available for research and machine learning
- [NVIDIA/DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples) - State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
- [fastai/course-nlp](https://github.com/fastai/course-nlp) - A Code-First Introduction to NLP course
- [graykode/nlp-tutorial](https://github.com/graykode/nlp-tutorial) - Natural Language Processing Tutorial for Deep Learning Researchers
- [fastai/fastai](https://github.com/fastai/fastai) - The fastai deep learning library
- [CME211/notes](https://github.com/CME211/notes) - CME211 Notes
- [virgili0/Virgilio](https://github.com/virgili0/Virgilio) - Your new Mentor for Data Science E-Learning.
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