https://www.quora.com/How-do-I-learn-machine-learning-1?redirected_qid=6578644   How Can I Learn X? Learning Machine Learning Learning About Computer Science Educational Resources Advice Artificial Intelligence How-to Question Learning New Things Lea…

在Github上也po了这个系列学习笔记(MachineLearningCourseNote),觉得写的不错的小伙伴欢迎来给项目点个赞哦~~ ML Lecture 0-2: Why we need to learn machine learning? Why we need to learn ML Many people think: Wow!!! AI is so powerful right now! You see AlphaGO? AI is going to replace human…

Decision Boundaries for Deep Learning and other Machine Learning classifiers H2O, one of the leading deep learning framework in python, is now available in R. We will show how to get started with H2O, its working, plotting of decision boundaries and…

前言 由于实验原因,准备入坑 python 机器学习,而 python 机器学习常用的包就是 scikit-learn ,准备先了解一下这个工具.在这里搜了有 scikit-learn 关键字的书,找到了3本:<Learning scikit-learn: Machine Learning in Python><Mastering Machine Learning With scikit-learn><scikit-learn Cookbook>,第一本是2013年出版…

一.Training of a Single-Layer Neural Network 1 Delta Rule Consider a single-layer neural network, as shown in Figure 2-11. In the figure, d i is the correct output of the output node i. Long story short, the delta rule adjusts the weight as the follow…

问题情形 使用Python SDK在连接到数据库后,连接数据库获取数据成功,但是在Pandas中用 to_sql 反写会数据库时候报错.错误信息为:ProgrammingError: ('42000', "[42000] [Microsoft][SQL Server Native Client 11.0][SQL Server]Invalid object name 'sqlite_master'. (104014) (SQLExecDirectW)"). 出错代码片段: import…

Method Feature(s) Sample(s) Result Value/Feature Permutation Importance 1 all validation samples Single Scale Partial Dependence Plots 1~2 all validation samples Vector(reasults vs feature) SHAP Values N individual sample 每个feature对当前结果的贡献(相对于baselin…

Preface 模式识别这个词,以前一直不懂是什么意思,直到今年初,才开始打算读这本广为推荐的书,初步了解到,它的大致意思是从数据中发现特征,规律,属于机器学习的一个分支. 在前言中,阐述了什么是模式识别之后,立刻就提到了贝叶斯方法,感觉贝叶斯方法在模式识别中有一个特别重要的位置.至于为什么,我现在还没体会到. 随后又提到了几个术语:approximate inference algorithms.variational Bayes.expectation propagation,以及model…

引言: 最近开始学习"机器学习",早就听说祖国宝岛的李宏毅老师的大名,一直没有时间看他的系列课程.今天听了一课,感觉非常棒,通俗易懂,而又能够抓住重点,中间还能加上一些很有趣的例子加深学生的印象. 视频链接(bilibili):李宏毅机器学习(2017) 另外已经有有心的同学做了速记并更新在github上:李宏毅机器学习笔记(LeeML-Notes) 所以,接下来我的笔记只记录一些我自己的总结和听课当时的困惑,如果有能够帮我解答的朋友也请多多指教. 李老师这一集仅用1分19秒时间,通过…

Why ML stategy 怎么提高预测准确度?有了stategy就知道从哪些地方入手,而不至于找错方向做无用功. Satisficing and Optimizing metric 上图中,running time <= 100ms 就是satisficing,accuracy 就是 optimazing. Dev set and test set should be from same distribution. 传统的traing set/ dev set / test set 比例是6…

1. active learning Active learning 是一种特殊形式的半监督机器学习方法,该方法允许交互式地询问用户(或者其他形式的信息源 information source)以获取对新的数据样本的理想输出. Active learning 提供的这种交互机制尤其适用于 unlabeled data 有很多,且手工标注的代价十分高昂的场合.显然这种交互式地向用户询问以获取label,使得原始非监督问题变成了一种迭代式的监督学习(iterative supervised lear…

转自:http://my.oschina.net/u/175377/blog/84420#OSC_h2_23 Scikit Learn: 在python中机器学习 Warning 警告:有些没能理解的句子,我以自己的理解意译. 翻译自:Scikit Learn:Machine Learning in Python 作者: Fabian Pedregosa, Gael Varoquaux 先决条件 Numpy, Scipy IPython matplotlib scikit-learn 目录 载入…

https://www.quora.com/How-do-I-learn-mathematics-for-machine-learning   How do I learn mathematics for machine learning? Promoted by Time Doctor Software for productivity tracking. Time tracking and productivity improvement software with screenshots…

在<机器学习---线性回归(Machine Learning Linear Regression)>一文中,我们主要介绍了最小二乘线性回归算法以及简单地介绍了梯度下降法.现在,让我们来实践一下吧. 先来回顾一下用最小二乘法求解参数的公式:. (其中:,,) 再来看一下随机梯度下降法(Stochastic Gradient Descent)的算法步骤: 除了算法中所需的超参数α(学习速率,代码中写为lr)和epsilon(误差值),我们增加了另一个超参数epoch(迭代次数).此外,为方便起见,…

之前在<机器学习---感知机(Machine Learning Perceptron)>一文中介绍了感知机算法的理论知识,现在让我们来实践一下. 有两个数据文件:data1和data2,分别用于PLA和Pocket Algorithm.可在以下地址下载:https://github.com/RedstoneWill/MachineLearningInAction/tree/master/Perceptron%20Linear%20Algorithm/data. 先回顾一下感知机算法: 1,初始…

昨天总结了深度学习的资料,今天把机器学习的资料也总结一下(友情提示:有些网站需要"科学上网"^_^) 推荐几本好书: 1.Pattern Recognition and Machine Learning (by Hastie, Tibshirani, and Friedman's ) 2.Elements of Statistical Learning(by Bishop's) 这两本是英文的,但是非常全,第一本需要有一定的数学基础,第可以先看第二本.如果看英文觉得吃力,推荐看一下下面…

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). 1. C++ 1.1 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 OpenCV—它提供C++, C, Python, Java 以及 MATLAB接口,并支持Windows, Linux, Android and Mac OS操作系统. 1.2 机器学习 MLPack DLib ecogg shark 2. Closure Closure Toolbox—Clojure语言库与工具的分类目录 3…

<Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机.神经网络.决策树.SVM.Adaboost到随机森林.Deep Learning. <Deep Learning in Neural Networks: An Overview> 介绍:这是瑞士人工智能实验室Jurgen Schmidhuber写的最新版本<神经网络与深度学习综述>本综述的特点是以时间排序,从1940年开始讲起,到60-80…

<Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机.神经网络.决策树.SVM.Adaboost 到随机森林.Deep Learning. <Deep Learning in Neural Networks: An Overview> 介绍:这是瑞士人工智能实验室 Jurgen Schmidhuber 写的最新版本<神经网络与深度学习综述>本综述的特点是以时间排序,从 1940 年开始讲起,到…

转自:机器学习(Machine Learning)&深度学习(Deep Learning)资料 <Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机.神经网络.决策树.SVM.Adaboost到随机森林.Deep Learning. <Deep Learning in Neural Networks: An Overview> 介绍:这是瑞士人工智能实验室Jurgen Schmidhuber写的最…

##机器学习(Machine Learning)&深度学习(Deep Learning)资料(Chapter 2)---#####注:机器学习资料[篇目一](https://github.com/ty4z2008/Qix/blob/master/dl.md)共500条,[篇目二](https://github.com/ty4z2008/Qix/blob/master/dl2.md)开始更新------#####希望转载的朋友**一定要保留原文链接**,因为这个项目还在继续也在不定期更新．希望看到…

About me In my spare time, I love learning new technologies and going to hackathons. Our hackathon project Pantrylogs using Artificial Intelligence was selected as one of the 10 Microsoft Imagine Cup UK finalists. I’m interested in learning more abou…

Machine Learning Crash Course  |  Google Developers https://developers.google.com/machine-learning/crash-course/ Google's fast-paced, practical introduction to machine learning ML Concepts Introduction to Machine Learning As you'll discover, machine…

Awesome系列 Awesome Machine Learning Awesome Deep Learning Awesome TensorFlow Awesome TensorFlow Implementations Awesome Torch Awesome Computer Vision Awesome Deep Vision Awesome RNN Awesome NLP Awesome AI Awesome Deep Learning Papers Awesome 2vec Deep…

In this post we take a tour of the most popular machine learning algorithms. It is useful to tour the main algorithms in the field to get a feeling of what methods are available. There are so many algorithms available and it can feel overwhelming whe…

5 Techniques To Understand Machine Learning Algorithms Without the Background in Mathematics Where does theory fit into a top-down approach to studying machine learning? In the traditional approach to teaching machine learning, theory comes first req…

转载:http://dataunion.org/8463.html?utm_source=tuicool&utm_medium=referral <Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机.神经网络.决策树.SVM.Adaboost到随机森林.Deep Learning. <Deep Learning in Neural Networks: An Overview> 介绍:这是瑞士人工智…

转载:http://www.jianshu.com/p/b73b6953e849 该资源的github地址:Qix <Statistical foundations of machine learning> 介绍:<机器学习的统计基础>在线版,该手册希望在理论与实践之间找到平衡点,各主要内容都伴有实际例子及数据,书中的例子程序都是用R语言编写的. <A Deep Learning Tutorial: From Perceptrons to Deep Networks>…

机器学习(Machine Learning)&深度学习(Deep Learning)资料 機器學習.深度學習方面不錯的資料,轉載. 原作:https://github.com/ty4z2008/Qix/blob/master/dl.md 原作作者會不斷更新.本文更新至2014-12-21 <Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍非常全面.从感知机.神经网络.决策树.SVM.Adaboost到随机森林.Deep L…

About this Course Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly i…