A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
- agentic-ai
- agentic-rag
- agents
- rag
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OmniGen: Unified Image Generation. https://arxiv.org/pdf/2409.11340
- diffusion
- image
- image-generation
- multi-modal
Genome modeling and design across all domains of life
[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models
- decision-making
- large-language-models
- llm
- prompting
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
- machine-learning
- pattern-classification
- machine-learning-algorithms
Everything you need to know to build your own RAG application
- agentic-rag
- chatbot
- llm
- machine-learning
Build a modern LLM from scratch. Every line commented. Explained like we are five.
- attention-mechanism
- deep-learning
- educational
- from-scratch
A collection of guides and examples for the Gemma open models from Google.
- codegemma
- gemma
- paligemma
- recurrentgemma
A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm
- anki-addon
- spaced-repetition-algorithm
- anki
- deep-learning
Qwen3-omni is a natively end-to-end, omni-modal LLM developed by the Qwen team at Alibaba Cloud, capable of understanding text, audio, images, and video, as well as generating speech in real time.
TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
- time-series
- time-series-forecasting
- deep-learning
- forecasting
A simplified implemention of Faster R-CNN that replicate performance from origin paper
- pytorch
- object-detection
- faster-rcnn
- voc
Text recognition (optical character recognition) with deep learning methods, ICCV 2019
- iccv2019
- ocr
- ocr-recognition
- text-recognition
This is a Phi Family of SLMs book for getting started with Phi Models. Phi a family of open sourced AI models developed by Microsoft. Phi models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks
- phi3
- phi3-testing
- phi3-vision
- phi4
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
- deep-reinforcement-learning
- qlearning
- deep-learning
- tensorflow-tutorials
PyTorch入门教程，在线阅读地址：https://datawhalechina.github.io/thorough-pytorch/
- deep-learning
- machine-learning
- python
- pytorch
This is Andrew NG Coursera Handwritten Notes.
- andrewng
- andrew-ng
- andrew-ng-course
- andrew-ng-machine-learning
中文nlp解决方案(大模型、数据、模型、训练、推理)
- bert
- nlp
- transformers
- gpt2
Book_5_《统计至简》 | 鸢尾花书：从加减乘除到机器学习；上架！
- machine-learning
- multivariate-statistics
- pca
- regression
Jupyter notebooks from the scikit-learn video series
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
- estimation
- perception
- robotics
- sensorfusion
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
- python
- machine-learning
- deep-learning
- pytorch
TensorFlow 最新官方文档中文版