VIP会员
作者:CSDN
出版社:CSDN《程序员》
ISBN:1111111111117
VIP会员免费
(仅需0.8元/天)
¥ 40000.0
温馨提示: 价值40000元的1000本电子书,VIP会员随意看哦!
电子书推荐
-
understanding machine learning-from theory to algorithms 评分:
2014年剑桥大学最新机器学习教材,讲解全面透彻,适合有一定基础的同学阅读。另附三本经典的机器学习教材:PRML,MLAPP以及统计学习方法。
上传时间:2015-02 大小:49.62MB
- 2.85MB
understanding machine learning
2015-03-30The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics of the field, the book covers a wide array of central topics that have not been addressed by previous textbooks.
- 3.1MB
Understanding Machine Learning: From Theory to Algorithms
2018-08-01Understanding Machine Learning: From Theory to Algorithms
- 2.48MB
understanding-machine-learning-theory-algorithms
2016-10-31understanding-machine-learning-theory-algorithms
- 2.41MB
understanding machine learning theory-algorithms
2019-10-131 Introduction 19 1.1 What Is Learning? 19 1.2 When Do We Need Machine Learning? 21 1.3 Types of Learning 22 1.4 Relations to Other Fields 24 1.5 How to Read This Book 25 1.5.1 Possible Course Plans Based on This Book 26 1.6 Notation 27 Part I Foundations 31 2 A Gentle Start 33 2.1 A Formal Model { The Statistical Learning Framework 33 2.2 Empirical Risk Minimization 35 2.2.1 Something May Go Wrong { Overtting 35 2.3 Empirical Risk Minimization with Inductive Bias 36 2.3.1 Finite Hypothesis Classes 37 2.4 Exercises 41 3 A Formal Learning Model 43 3.1 PAC Learning 43 3.2 A More General Learning Model 44 3.2.1 Releasing the Realizability Assumption { Agnostic PAC Learning 45 3.2.2 The Scope of Learning Problems Modeled 47 3.3 Summary 49 3.4 Bibliographic Remarks 50 3.5 Exercises 50 4 Learning via Uniform Convergence 54 4.1 Uniform Convergence Is Sucient for Learnability 54 4.2 Finite Classes Are Agnostic PAC Learnable 55 Understanding Machine Learning, c 2014 by Shai Shalev-Shwartz and Shai Ben-David Published 2014 by Cambridge University Press. Personal use only. Not for distribution. Do not post. Please link to http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning x Contents 4.3 Summary 58 4.4 Bibliographic Remarks 58 4.5 Exercises 58 5 The Bias-Complexity Tradeo 60 5.1 The No-Free-Lunch Theorem 61 5.1.1 No-Free-Lunch and Prior Knowledge 63 5.2 Error Decomposition 64 5.3 Summary 65 5.4 Bibliographic Remarks 66 5.5 Exercises 66 6 The VC-Dimension 67 6.1 Innite-Size Classes Can Be Learnable 67 6.2 The VC-Dimension 68 6.3 Examples 70 6.3.1 Threshold Functions 70 6.3.2 Intervals 71 6.3.3 Axis Aligned Rectangles 71 6.3.4 Finite Classes 72 6.3.5 VC-Dimension and the Number of Parameters 72 6.4 The Fundamental Theorem of PAC learning 72 6.5 Proof of Theorem 6.7 73 6.5.1 Sauer's Lemma and the Growth Function 73 6.5.2 Uniform Convergence for Classes of Small Eective Size 75 6.6 Summary 78 6.7 Bibliographic remarks 78 6.8 Exercises 78 7 Nonuniform Learnability 83 7.1
- 2.81MB
Understanding Machine Learning - From Theory to Algorithms
2018-06-25Understanding Machine Learning - From Theory to Algorithms 英文版
- 2.85MB
Understanding Machine Learning: From Theory to Algorithms
2019-04-27Understanding Machine Learning: From Theory to Algorithms.2014剑桥大学教材
- 2.42MB
Understanding Machine Learning - From Theory to Algorithms.zip
2019-07-08Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer ...
- 2.80MB
UNDERSTANDING MACHINE LEARNING From Theory to Algorithms
2017-11-07非扫描、高清版本 UNDERSTANDING MACHINE LEARNING From Theory to Algorithms Shai Shalev-Shwartz The Hebrew University, Jerusalem Shai Ben-David University of Waterloo, Canada
- 543KB
understand machine learning theory to algorithm
2019-01-01the exercise solution for book ' understanding machine learning from theory to algorithms. 作者Shai Shalev-Shwartz 和 Shai Ben-David
- 286KB
将卷积运算转换成矩阵相乘
2011-09-13本程序将一般的卷积运算心矩阵相乘的形式给出,并且可以心大矩阵的形式来显示卷积核的内容。
- 30KB
二维离散卷积及具体实例
2018-10-21该文档包括卷积运算的定义及其具体实例,以便读者更好的理解
- 491KB
相同大小二维矩阵卷积
2010-07-26二维矩阵卷积,两个图像大小相同 二维矩阵卷积,两个图像大小相同
- 23KB
二维卷积的c实现,很好的算法
2008-10-29二维卷积的c语言实现,若x为N1*M1的二维信号,y为N2*M2的二维信号,则卷积为(N1+N2-1)*(M1+M2-1)的信号 z(i,j)=∑ ∑x(m,n)y(i-m,j-n) m n
- 22.20MB
Pro Machine Learning Algorithms Implementing Algorithms in Python
2018-07-01Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R by V Kishore Ayyadevara Bridge the gap between a high-level understanding of how an algorithm works and...
- 45.20MB
Hands-On Machine Learning with Scikit-Learn and TensorFlow
2017-12-28The book favors a hands-on approach, growing an intuitive understanding of Machine Learning through concrete working examples and just a little bit of theory. While you can read this book without ...
- 23.27MB
Pro Machine Learning Algorithms Implementing Algorithms in Python epub
2018-07-01Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R by V Kishore Ayyadevara Bridge the gap between a high-level understanding of how an algorithm works and...
- 20.45MB
Mastering Java Machine Learning
2017-07-13More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-...
- 27.76MB
Machine Learning for OpenCV-Packt Publishing(2017).pdf
2018-04-03Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. As a subfield of data ...
- 1.18MB
Basics of Linear Algebra for Machine Learning
2018-12-30This book was designed around major data structures, operations, and techniques in linear algebra that are directly relevant to machine learning algorithms. There are a lot of things you could learn ...
- 1.18MB
Basics of Linear Algebra for Machine Learning (Python)
2019-01-16This book was designed around major data structures, operations, and techniques in linear algebra that are directly relevant to machine learning algorithms. There are a lot of things you could learn ...
- 11.46MB
Machine Learning Using R [2017]
2016-12-24Data scientists, data science professionals and researchers in academia who want to understand the nuances of Machine learning approaches/algorithms along with ways to see them in practice using R....
- 8.89MB
Vector Davinci官方帮助配置使用手册(AutoSAR).pdf
2019-08-19Vector官方帮助文档,配置使用手册。从新建DaVinci工程开始一步一步的讲解如何配置工程;如何编译生成C代码;如何导入CDD、DBC等文件。手册讲解细致,可以说是手把手教学了
- 5.6MB
c++入门,核心,提高讲义笔记
2021-11-27最详细的c++入门,核心,提高讲义笔记,看会成为大佬没问题,下载后有疑问请私信。
- 75.21MB
离散数学及其应用 第八版 奇数编号练习答案.pdf
2021-01-23离散数学及其应用 第八版本科教学版答案,有需要其他版本到的还可以去华章图书官网下载 地址:http://www.hzbook.com/
- 6.21MB
数字图像处理 冈萨雷斯 课后习题
2020-09-28数字图像处理 冈萨雷斯 第三版 课后习题。 免费下,没积分的朋友们,免费下。 百度文库网页链接转出来的,清晰,内容可能不太全,没积分的朋友们将就看吧。
- 1.45MB
科研伦理与学术规范 期末考试2 (40题).pdf
2020-12-30科研伦理与学术规范 期末考试2 (40题)
- 248KB
最值得收藏的 考研线性代数 全部知识点思维导图整理(张宇, 汤家凤), 附带惯用思维/做题技巧/易错点整理.emmx
2021-03-27用mindmaster打开文件,本文的思维导图根据张宇和汤家凤两人的课程整理而来并标记出重点内容,整合了很多技巧,题型,方法
- 24KB
软件著作权设计说明书模板(含填写说明).docx
2020-12-24软件著作权最新版设计说明书,每项都有填写说明,可供新人参考。
- 23.84MB
AUTOSAR培训教材.rar
2019-12-09AUTOSAR培训教材,共25.7M,17个PDF文件,十分详细,适合自学或者培训使用。 主要内容:00_AUTOSAR基础知识介绍、01_SWC应用层组件设计详解、02_OS操作系统详解、03_Communication Stack详解、04_Diagnosis Stack 详解、05_Mem Stack详解、06_IO Stack详解、07_WdgM Stack 详解、08_EcuM BswM系统服务详解、09_MCAL详解、10_RTE设计详解、11_传统软件到AUTOSAR移植解决方案、12_基于模型MBD开发的AUTOSAR解决方案、13_多核AUTOSAR架构的解决方案、14_功能安全在AUTOSAR中的解决方案、15_信息安全在AUTOSAR中的解决方案、16_Adaptive AUTOSAR。希望对大家有所帮助。