Translated《动手学深度学习》 (Dive into Deep Learning): for Chinese readers, runnable, and open to discussion. The Chinese and English editions are used for teaching at more than 500 universities in more than 70 countries.
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Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
TranslatedThis project changes the MXNet implementations in the original book 《动手学深度学习》 (Dive into Deep Learning) into PyTorch implementations.
- deep-learning
- deep-learning-tutorial
- pytorch
- pytorch-tutorial
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
- pytorch
- pytorch-tutorials
- pytorch-tutorials-cn
- deep-learning
An open access book on scientific visualization using python and matplotlib
- python
- matplotlib
- dataviz
- scientific-publications
TranslatedBook_4_"The Power of Matrices" | Iris Book: From Addition, Subtraction, Multiplication and Division to Machine Learning; now on sale!
TranslatedDeep learning interview handbook (covering mathematics, machine learning, deep learning, computer vision, natural language processing, SLAM, and more)
TranslatedBook_3_"Elements of Mathematics" | Iris Book series: from addition, subtraction, multiplication and division to machine learning; now on sale; corrections are still welcome, and readers who submit many corrections will also receive free books!
Become a cracked AI/ML researcher/engineer with this unconventional textbook covering maths, computing, and ML with intuition.
TranslatedBook_1_《Programming Is Not Hard》 | Iris Book: From Addition, Subtraction, Multiplication and Division to Machine Learning; please give us plenty of criticism and corrections!
TranslatedRUN · 润 (Run, "to slip away; to emigrate"): A handbook for overseas relocation for Chinese passport holders. 110 immigration routes across 36 European countries + 13 major immigration regions: digital nomad visas, EU Blue Card, skilled migration, study-to-work, entrepreneurship and self-employment, investment residency, each with official sources, continuously updated.
- china
- chinese
- digital-nomad
- digital-nomad-visa
Translated"PyTorch Practical Tutorial" (Second Edition): whether you are starting from zero, working on CV, NLP, or LLM project applications, or moving on to advanced engineering deployment, it's all here. We believe that with the help of this book, readers will be able to master the use of PyTorch with ease and become an excellent deep learning engineer.
- computer-vision
- deepsort
- diffusion-models
- onnx
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
- deep-learning
- d2l
- data-science
- pytorch-implmention
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
Book_2_《可视之美》 | 鸢尾花书：从加减乘除到机器学习，欢迎批评指正
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
”数学不难“ 之 《线性代数不难》上下册，66话题完册；欢迎批评指正
A book covering the fundamentals of data visualization
Book_7_《机器学习》 | 鸢尾花书：从加减乘除到机器学习；欢迎批评指正
A computer vision closed-loop learning platform where code can be run interactively online. 学习闭环《计算机视觉实战演练：算法与应用》中文电子书、源码、读者交流社区（持续更新中 ...） 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页
- tutorial
- charmve
- machine-learning
- computer-vision
Code for the book "Mastering OpenCV with Practical Computer Vision Projects" by Packt Publishing 2012.
Book_6_《数据有道》 | 鸢尾花书：从加减乘除到机器学习；欢迎大家批评指正！纠错多的同学会得到赠书感谢！
- data
- data-science
- data-visualization
- feature-engineering
常用书籍
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER