is no doubt that neural networks, and machine learning in general, has been one of the hottest topics

比较全面的收集了机器学习的介绍文章，从感知机、神经网络、决策树、SVM、Adaboost到随机森林、Deep Learning。 《机器学习经典论文/survey合集》 介绍：看题目你已经知道了是什么内容,没错

Wibi Data Views: 24 0 ratings Time: 47:08 More in Science & Technology Utilizing Transfer Learning for

Machine Learning 101: I. Introduction to Machine Learning http://homepages.inf.ed.ac.uk/rbf/IAPR/res

1. YAFIM: Frequent Itemset Mining with Spark Rong Gu, Hongjian Qiu, Yihua Huang Parallel Algorithm System

2. Outside the Closed World: On Using Machine Learning for Network Intrusion Detection 本文来自加州伯克利大学

基于模型（Model-Based）的聚类方法 8.9 孤立点分析 8.10 总结 2018/10/231Data Mining: Concepts and Techniques 2. 8.1什么是聚类分析?簇（Cluster）:一个数据对象的集合

for running statistical analysis over a (huge) set of time series The Long Term Prediction is the first

知识提取(knowledge extraction), 数据/模式分析(data/pattern analysis), 数据考古(data archeology), 数据捕捞(data dredging), 信息收获(information

Open source machine learning software makes it easier to implement machine learning solutions on single

Strings Lists Dictionaries Tuples - ordered list of elements Files Classes and objects / Classes and functions

Deep Machine Learning libraries and frameworks At the end of 2015, all eyes were on the year’s accomplishments

http://n-chandra.blogspot.com/2013/01/picking-machine-learning-algorithm.html ) 图4: 机器学习和其他学科的关系： 数据科学的地铁图

是一个机器学习API和服务器，采用 C++11开发。It makes state of the art machine learning easy to work with and integrate into existing

—供Node.js用的LDA主题建模工具。 Learning.js —逻辑回归/c4.5决策树的JavaScript实现 Machine Learning —Node.js的机器学习库。 Node-SVM

英文原文： awesome-machine-learning 本文汇编了一些机器学习领域的框架、库以及软件（按编程语言排序）。 C++ 计算机视觉 CCV —基于C语言/提供缓存/核心的机器视觉库，新颖的机器视觉库

motivated from two recent papers which did move prediction by training a network from professional game

Plotting and Visualization // Benchmarks // Python and "Data Science" // Other // Useful scripts and snippets

interface. github.com Shared by @whatthecarp mining github.com Shared by @mgrouchy wagtail

让深度学习变得更容易。 当然牛好吹，也是要做些实际行动的，所有便有了 spark-deep-learning 项目。这件事情已经有很多人尝试做了，但显然太浅了，DB公司则做的更深入些。 原理 要做