wangjiezhe
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written in Jupyter Notebook
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A latent text-to-image diffusion model
Python Data Science Handbook: full text in Jupyter Notebooks
12 Weeks, 24 Lessons, AI for All!
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Python programs, usually short, of considerable difficulty, to perfect particular skills.
100-Days-Of-ML-Code中文版
A High-Quality Real Time Upscaler for Anime Video
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
Companion webpage to the book "Mathematics For Machine Learning"
The "Python Machine Learning (1st edition)" book code repository and info resource
《Python Cookbook》 3rd Edition Translation
面向开发者的 LLM 入门教程，吴恩达大模型系列课程中文版
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
AISystem 主要是指AI系统，包括AI芯片、AI编译器、AI推理和训练框架等AI全栈底层技术
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
TensorFlow Tutorials with YouTube Videos
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
Simple tutorials using Google's TensorFlow Framework
Inpaint anything using Segment Anything and inpainting models.
Understanding Deep Learning - Simon J.D. Prince
Learn python3 in one picture.
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
Text and supporting code for Think Stats, 2nd Edition
Jupyter notebooks from the scikit-learn video series