Python Data Science Handbook: full text in Jupyter Notebooks
- scikit-learn
- numpy
- python
- jupyter-notebook
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Python Data Science Handbook: full text in Jupyter Notebooks
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 ;)
The fastai book, published as Jupyter Notebooks
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
Translated"Lee Hung-yi's Deep Learning Tutorial" (recommended by Professor Hung-yi Lee 👍, the Apple Book 🍎), PDF download address: https://github.com/datawhalechina/leedl-tutorial/releases
The "Python Machine Learning (1st edition)" book code repository and info resource
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
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!
The "Python Machine Learning (2nd edition)" book code repository and info resource
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
Text and supporting code for Think Stats, 2nd Edition
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
”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
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker
Code repository for O'Reilly book
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
HuggingLLM, Hugging Future.
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
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!
Tutorials, datasets, and other material associated with textbook "A First Course in Network Science" by Menczer, Fortunato & Davis