李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码李宏毅 机器学习 课程作业代码

mnist手写数字png-label测试和训练数据集；将ubyte文件转存为png将label存入txt。压缩包内有train和test两个文件夹。里面的内容是手写数字的图片和最后有一个label的txt。方便用matlab等做算法的人

The Elements of Statistical Learning中文+英文+练习答案

该数据是基于周志华的《机器学习》中数据自己制作的数据。

Hands-On Machine Learning with Scikit-Learn and TensorFlow_ Concepts, Tools高清版pdf

Hands-On Recommendation Systems with Python: Start building powerful and personalized, recommendation engines with Python Rounak Banik 201807 Packt Publishing

数据集合适合机器学习入门者的数据集合，可以用来进行特征提取，降维，基础算法测试。

模式分类 作者: Richard O. Duda / Peter E. Hart / David G. Stork ，李宏东 翻译 中文第二版

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. You’ll find recipes for: Vectors, matrices, and arrays Handling numerical and categorical data, text, images, and dates and times Dimensionality reduction using feature extraction or feature selection Model evaluation and selection Linear and logical regression, trees and forests, and k-nearest neighbors Support vector machines (SVM), naïve Bayes, clustering, and neural networks Saving and loading trained models

Python Data Science Handbook是一本优秀的python数据分析入门教材. 本资源中包含英文pdf文件和官方提供的Jupyter Notebook , 内含书上所有的代码和图表.