This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.
TensorFlow Tutorials with YouTube Videos
Collection of notebooks about quantitative finance, with interactive python code.
- quantitative-finance
- jupyter-notebooks
- kalman-filter
- option-pricing
TranslatedAI in Practice - practicalAI, Chinese version
- machine-learning
- jupyter-notebook
- pytorch
- google-colab-notebook
Translated【🔞🔞🔞 Contains images not suitable for minors】AI exploration and summary based on my strengths in programming, drawing, and writing: StableDiffusion is a powerful image generation model that can generate new images by evolving an existing image. ChatGPT is a Transformer-based language generation model that can automatically generate suitable articles for an input topic. And Github Copilot is an intelligent programming assistant that can speed up everyday programming activities.
- ai
- aigc
- chatgpt
- github-copilot
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services
- artificial-intelligence
- generative-ai
- kubernetes
- kustomize
TensorFlow Basic Tutorial Labs
- tensorflow
- keras
- mxnet
- pytorch
小型金融知识图谱构建流程（neo4j / python / cypher / KG）
- cypher
- data-analysis
- graph-database
- neo4j
FLUX, Stable Diffusion, SDXL, SD3, LoRA, Fine Tuning, DreamBooth, Training, Automatic1111, Forge WebUI, SwarmUI, DeepFake, TTS, Animation, Text To Video, Tutorials, Guides, Lectures, Courses, ComfyUI, Google Colab, RunPod, Kaggle, NoteBooks, ControlNet, TTS, Voice Cloning, AI, AI News, ML, ML News, News, Tech, Tech News, Kohya, Midjourney, RunPod
- dreambooth
- guides
- stable-diffusion
- tts
Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.
- mathematics
- linear-algebra
- python
- jupyter
An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
- milvus
- unstructured-data
- image-search
- audio-search
This repository helps you learn Python and Machine Learning from scratch.
- python
- jupyter-notebook
- pandas-dataframe
- numpy
Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!
- evaluation
- evaluation-metrics
- guidebook
- large-language-models
零知识证明入门教程。Comprehensive Zero-Knowledge Proofs Tutorial. #zk #WIP
- abstract-algebra
- bitcoin
- blockchain
- cryptography
Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE
100 days of LLM inference engineering — daily posts, experiments, and visualizations
Notebooks about Bayesian methods for machine learning
- machine-learning
- bayesian-methods
- bayesian-machine-learning
- gaussian-processes
Collection of notebook guides created by the Brev.dev team!
TeachOpenCADD: a teaching platform for computer-aided drug design (CADD) using open source packages and data
ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy