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A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Python programs, usually short, of considerable difficulty, to perfect particular skills.
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。
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
《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
Practice your pandas skills!
Deep Learning Specialization by Andrew Ng on Coursera.
《Pytorch实用教程》（第二版）无论是零基础入门，还是CV、NLP、LLM项目应用，或是进阶工程化部署落地，在这里都有。相信在本书的帮助下，读者将能够轻松掌握 PyTorch 的使用，成为一名优秀的深度学习工程师。
Code Repository for The Kaggle Book, Published by Packt Publishing
主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。
《深度学习入门-基于Python的理论与实现》，包含源代码和高清PDF(带书签)；慕课网imooc《深度学习之神经网络(CNN-RNN-GAN)算法原理-实战》；《菜菜的机器学习sklearn》
Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
A collection of code snippets from the publication Daily Dose of Data Science on Substack: http://www.dailydoseofds.com/
Inside Deep Learning: The math, the algorithms, the models
Learning Data Mining with Python Second Edition by Packt