12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
- ml
- data-science
- machine-learning
- machine-learning-algorithms
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12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Python Data Science Handbook: full text in Jupyter Notebooks
Learn how to develop, deploy and iterate on production-grade ML applications.
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. Join the course here 👇🏼
This is a repo with links to everything you'd ever want to learn about data engineering
10 Weeks, 20 Lessons, Data Science for All!
📚 从零开始构建大模型
《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
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Course Files for Complete Python 3 Bootcamp Course on Udemy
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
面向开发者的 LLM 入门教程,吴恩达大模型系列课程中文版
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Data and code behind the articles and graphics at FiveThirtyEight
《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
Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort
Your new Mentor for Data Science E-Learning.
Learn ML engineering for free in 4 months! Register here 👇🏼
强化学习中文教程(蘑菇书🍄),在线阅读地址:https://datawhalechina.github.io/easy-rl/
Python training for business analysts and traders
本项目是一个面向小白开发者的大模型应用开发教程,在线阅读地址:https://datawhalechina.github.io/llm-universe/