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Learning from data e-chapter 6 Similarity-Based Methods 7 Neural Networks 8 Support Vector Machines 9 Learning Aides 去除了水印 手工添加了书签
2018-01-19 上传大小:23.35MB
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[全] learning from data+e-chapters 机器学习基石/技法(林轩田)textbook

coursera ntu公开课 机器学习基石/机器学习技法 教材 learning from data实体书本身包含五章 e-chapters本身包含四章及附录,是本书线上部分章节(神经网络、svm等) pdf包含简单目录标签

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Learning from data 练习8.6(a)
Learning From Data plus 完整版带目录 林轩田

Learning From Data plus,完整版带目录,除了机器学习基石该门课配套的教材Learning from Data之外,还补充了后续林轩田老师提供的e-chapter内容 原版是从lbluesky01下载的,个人加上了完整的目录标签。 e-Chapter 6 Similarity-Based Methods e-Chapter 7 Neural Networks e-Chapter 8 Support Vector Machines e-Chapter 9 Learning Aides

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Learning From Data plus 超清完整版 林轩田(英文版)

Learning From Data plus,完整版,除了机器学习基石该门课配套的教材Learning from Data之外,还补充了后续林轩田老师提供的e-chapter内容(英文版) e-Chapter 6 Similarity-Based Methods e-Chapter 7 Neural Networks e-Chapter 8 Support Vector Machines e-Chapter 9 Learning Aides 如果你没有csdn币恰好也在学习这么课,欢迎加我QQ757387961我将免费发送

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机器学习记忆卡片(Learning from data 01)

个人做的Learning from data 记忆卡片。涉及VC维度,variance, bias,霍夫丁不等式等topic。建议配合书看完Chapter1和Chapter2(重点)使用。

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Learning Cocoa with Objective-C, 4th Edition

Get up to speed on Cocoa and Objective-C, and start developing applications on the iOS and OS X platforms. If you don’t have experience with Apple’s developer tools, no problem! From object-oriented programming to storing app data in iCloud, the fourth edition of this book covers everything you need

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Learning Data Mining with Python - Second Edition

earning Data Mining with Python - Second Edition by Robert Layton English | 4 May 2017 | ASIN: B01MRP7VFV | 358 Pages | AZW3 | 2.85 MB Key Features Use a wide variety of Python libraries for practical data mining purposes. Learn how to find, manipulate, analyze, and visualize data using Python. St

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Machine-Learning-in-Python-Essential-Techniques-for-Predictive-Analysis

This book covers two broad classes of machine learning algorithms: penalized linear regression (for example, Ridge and Lasso) and ensemble methods (for example, Random Forests and Gradient Boosting). Each of these families contains variants that will solve regression and classifcation problems. (You

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Data Mining - Concepts, Models, Methods, and Algorithms

内容丰富,数据挖掘经典书籍 目录如下 Chapter 1 - Data-Mining Concepts Chapter 2 - Preparing the Data Chapter 3 - Data Reduction Chapter 4 - Learning from Data Chapter 5 - Statistical Methods Chapter 6 - Cluster Analysis Chapter 7 - Decision Trees and Decision Rules Chapter 8 - Association Rules Chapt

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Introduction to Data Science - A Python Approach

This book is an introduction to concepts, techniques, and applications in data science. This book focuses on the analysis of data, covering concepts from statistics to machine learning, techniques for graph analysis and parallel programming, and applications such as recommender systems or sentiment

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Pandas for Everyone Python Data Analysis -2018.pdf

Contents Chapter 1. Pandas Dataframe basics 1.1 Introduction 1.2 Concept map 1.3 Objectives 1.4 Loading your first data set 1.5 Looking at columns, rows, and cells 1.6 Grouped and aggregated calculations 1.7 Basic plot 1.8 Conclusion Chapter 2. Pandas data structures 2.1 Introduction 2.2 Concept map

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Mastering Machine Learning with scikit-learn -2017.7.24

Book Description Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model. This book examines a variety of machine learning model

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data-structures-algorithms-go

Data Structures and Algorithms in Go Written byBill Broughton This book is just getting started and doesn't have much content yet. Stay tuned. Learning data structures and algorithms is the next step in improving programming skills. Sound knowledge of data structures and algorithms will allow you

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Pro-Deep-Learning-with-TensorFlow.pdf

Pro Deep Learning with TensorFlow is a practical and mathematical guide to deep learning using TensorFlow. Deep learning is a branch of machine learning where you model the world in terms of a hierarchy of concepts. This pattern of learning is similar to the way a human brain learns, and it allows c

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Complete Guide to Open Source Big Data Stack-Apress(2018).pdf

I have developed this book to investigate Mesos-based cluster development and integration. I found that data center operating system (DCOS; and it’s command-line interface [CLI]) was a natural progression from basic Mesos; so you will find that the later chapters of this book concentrate on

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Machine Learning and Data Mining for Computer Security

Intrusion detection and analysis has received a lot of criticism and publicity over the last several years. The Gartner report took a shot saying Intrusion Detection Systems are dead, while others believe Intrusion Detection is just reaching its maturity. The problem that few want to admit is that t

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Haskell is trending in the field of data science by providing a powerful platform for robust data science practices. This book provides you with the skills to handle large amounts of data, even if that data is in a less than perfect state. Each chapter in the book helps to build a small library of c

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Learning.Data.Mining.with.Python.1784396052

Harness the power of Python to analyze data and create insightful predictive models About This Book Learn data mining in practical terms, using a wide variety of libraries and techniques Learn how to find, manipulate, and analyze data using Python Step-by-step instructions on creating real-world ap

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When most people hear “Machine Learning,” they picture a robot: a dependable butler or a deadly Terminator depending on who you ask. But Machine Learning is not just a futuristic fantasy, it’s already here. In fact, it has been around for decades in some specialized applications, such as Optical Cha

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