Hands on Machine Learning with Scikit Learn and TensorFlow 英文原版 彩色配图

Unsupervised Learning: Deep Auto-encoder Auto-encoder Deep Auto-encoder Auto-encoder – Text Retrieval Auto-encoder – Similar Image Search Auto-encoder for CNN CNN -Unpooling CNN - Deconvolution

新网银行的统计建模比赛，使用xgboost +lr模型融合，先用xgboost提取特征，再使用lr分类。

斯坦福大学吴恩达2014机器学习个人笔记完整版v5.3-A4打印版

Python Machine Learning 第二版 Sebastian Raschka著 高清带书签

压缩包包含Machine Learning in Action数据的中英文版本及书籍配套源代码，让我们一起走进ML的世界。

行业分类-网络游戏-M-Learning无线网络学习系统.zip

介绍了经典的机器学习算法，包括决策树，随机森林，逻辑回归，SVM等八种算法及python代码

Python_Machine_Learning_By_Example 原书高清pdf 及随书代码

Welcome to Machine Learning Algorithms From Scratch. This is your guide to learning the details of machine learning algorithms by implementing them from scratch in Python. You will discover how to load data, evaluate models and implement a suite of top machine learning algorithms using step-by-step tutorials and sample code. Machine learning algorithms do have a lot of math and theory under the covers, but you do not need to know why algorithms work to be able to implement them and apply them to achieve real and valuable results. From an applied perspective, machine learning is a shallow field and a motivated developer can quickly pick it up and start making very real and impactful contributions. This is my goal for you and this book is your ticket to that outcome.