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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 ;)
TranslatedThis project changes the MXNet implementations in the original book 《动手学深度学习》 (Dive into Deep Learning) into PyTorch implementations.
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》)
TranslatedBook_4_"The Power of Matrices" | Iris Book: From Addition, Subtraction, Multiplication and Division to Machine Learning; now on sale!
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
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!
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!
Python code for "Probabilistic Machine learning" book by Kevin Murphy
"Probabilistic Machine Learning" - a book series by Kevin Murphy
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
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.
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
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
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！
深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI
”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
Tutorials, datasets, and other material associated with textbook "A First Course in Network Science" by Menczer, Fortunato & Davis