很好的的深度学习材料，值得与大家分享，讲解非常详细~

xgboost是一种集成学习中非常厉害的算法，在kaggle等比赛中取得了非常好的成绩。资源中有作者陈天奇的论文及ppt详解。

搜索方法合集，优化算法大全，大师之作，本书提供了大量的完整的先进的优化搜索算法，希望能给读者带来帮助和启示

自己做的课后编程练习，都顺利通过了，且有不同解法，对初学的同学不失为一个参考

Structured Learning Unified Framework Unified Framework – Object Detection Unified Framework - Summarization Unified Framework - Retrieval Structured Linear Model

Learning A Bayesian and Optimization Perspective 英文原版书籍，高清带目录，非扫描版

Complex statistics in machine learning worry a lot of developers. Knowing statistics helps you build strong machine learning models that are optimized for a given problem statement. I believe that any machine learning practitioner should be proficient in statistics as well as in mathematics, so that they can speculate and solve any machine learning problem in an efficient manner. In this book, we will cover the fundamentals of statistics and machine learning, giving you a holistic view of the application of machine learning tech niques for relevant problems. We will discuss the application of frequently used algorithms on various domain problems, using both Python and R programming. We will use libraries such as scikit-learn, e1071, randomForest, c50, xgboost, and so on. We will also go over the fundamentals of deep learning with the help of Keras software. Furthermore, we will have an overview of reinforcement learning with pure Python programming language. The book is motivated by the following goals: To help newbies get up to speed with various fundamentals, whilst also allowing experienced professionals to refresh their knowledge on various concepts and to have more clarity when applying algorithms on their chosen data. To give a holistic view of both Python and R, this book will take you through various examples using both languages. To provide an introduction to new trends in machine learning, fundamentals of deep learning and reinforcement learning are covered with suitable examples to teach you state of the art techniques.

The Hundred-Page Machine Learning Book 原版英文书籍前3章；作者：Andriy Burkov

决策树和随机森林-邹伟的ppt，适用于机器学习爱好者。

分位数回归森林论文，基于随机森林，可进行分位数回归预测