bnufw
Follow
Stars
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
12 Weeks, 24 Lessons, AI for All!
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程
Understanding Deep Learning - Simon J.D. Prince
Pytorch🍊🍉 is delicious, just eat it! 😋😋
Materials for the Hugging Face Diffusion Models Course
《Pytorch实用教程》（第二版）无论是零基础入门，还是CV、NLP、LLM项目应用，或是进阶工程化部署落地，在这里都有。相信在本书的帮助下，读者将能够轻松掌握 PyTorch 的使用，成为一名优秀的深度学习工程师。
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
仅需Python基础，从0构建大语言模型；从0逐步构建GLM4\Llama3\RWKV6， 深入理解大模型原理
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.
Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
DiffusionFastForward: a free course and experimental framework for diffusion-based generative models
Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)
This is a tutorial to connect the fundamental mathematics to a practical implementation addressing the continual learning problem of artificial intelligence
Continual Learning tutorials and demo running on Google Colaboratory.
Solutions to the problems in the book: Linear Algebra and Learning from Data by Gilbert Strang, MIT
Personal short implementations of Machine Learning papers
[ICLR 2024] MogaNet: Efficient Multi-order Gated Aggregation Network
A project for text-to-image remote sensing image generation.
Satellite cloud removal with Deep Image Prior.
Removing cloud cover in Sentinel-2 satellite images using only optical data and a novel augmented training approach using conditional GANs.