Python machine learning

This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossles

Digitization is reshaping our careers, companies, and industries. Machine learning, artificial intelligence, and robotics are surpassing human capabilities across broad sectors of the economy but also

Packed with detailed examples and illustrations, PRECISION MACHINING TECHNOLOGY, Third Edition, is your ideal introduction to today's machine tool industry, equipping you with a solid understanding of

The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classi

Stochastic differential equations are differential equations whose solutions are stochastic processes. They exhibit appealing mathematical properties that are useful in modeling uncertainties and noisy phenomena in many disciplines. This book is motivated by applications of stochastic differential equations in target tracking and medical technology and, in particular, their use in methodologies such as filtering, smoothing, parameter estimation, and machine learning. It builds an intuitive hands-on understanding of what stochastic differential equations are all about, but also covers the essentials of Itô calculus, the central theorems in the field, and such approximation schemes as stochastic Runge–Kutta. Greater emphasis is given to solution methods than to analysis of theoretical properties of the equations. The book's practical approach assumes only prior understanding of ordinary differential equations. The numerous worked examples and end-of-chapter exercises include application-

Stochastic differential equations are differential equations whose solutions are stochastic processes. They exhibit appealing mathematical properties that are useful in modeling uncertainties and noisy phenomena in many disciplines. This book is motivated by applications of stochastic differential equations in target tracking and medical technology and, in particular, their use in methodologies such as filtering, smoothing, parameter estimation, and machine learning. It builds an intuitive hands-on understanding of what stochastic differential equations are all about, but also covers the essentials of Itô calculus, the central theorems in the field, and such approximation schemes as stochastic Runge–Kutta. Greater emphasis is given to solution methods than to analysis of theoretical properties of the equations. The book's practical approach assumes only prior understanding of ordinary differential equations. The numerous worked examples and end-of-chapter exercises include application-

Artificial intelligence and related technologies are changing both the law and the legal profession. In particular, technological advances in fields ranging from machine learning to more advanced robo

This book will provide an introduction to machine learning, fuzzy systems and evolutionary algorithms for senior undergraduate students at universities and colleges as well as for practitioners. The t

本書基於Azure Machine Learning Studio探討了現代數據科學算法的背景、理論和實際應用。 全書共8章。第1章描述了在數據科學領域，Azure機器學習如何通過實現完全託管的數據科學雲服務邁出預測分析解決方案的關鍵一步；第2章講解預測分析科學和方法論的基本概念；第3章探討Azure ML Studio的基本原理；第4章基於一個實用的Azure機器學習預測模型，探討可以用來調用A

This SpringerBrief covers the technical material related to large scale hierarchical classification (LSHC). HC is an important machine learning problem that has been researched and explored extensivel

Create applications using Industry 4.0. Discover how artificial intelligence (AI) and machine learning (ML) capabilities can be enhanced using the Internet of things (IoT) and secured using Blockchain

This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and

This book offers an introduction to modern natural language processing using machine learning, focusing on how neural networks create a machine interpretable representation of the meaning of natural l

In spite of intense but traditional academic effort, a unique formal framework to study civil conflict has been elusive. This book uses predictive machine learning to highlight a framework to identify

Recent startling successes in machine intelligence using a technique called ‘deep learning’ seem to blur the line between human and machine as never before. Are computers on the cusp of be

Recent startling successes in machine intelligence using a technique called ‘deep learning’ seem to blur the line between human and machine as never before. Are computers on the cusp of be

An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts a

This book shows machine learning enthusiasts and practitioners how to get the best of both worlds by deriving Fisher kernels from deep learning models. In addition, the book shares insight on how to s

This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra. Requiring no prior knowledge of the subject, it covers the aspects of linear algebra - vectors, matrices, and least squares - that are needed for engineering applications, discussing examples across data science, machine learning and artificial intelligence, signal and image processing, tomography, navigation, control, and finance. The numerous practical exercises throughout allow students to test their understanding and translate their knowledge into solving real-world problems, with lecture slides, additional computational exercises in Julia and MATLAB®, and data sets accompanying the book online. Suitable for both one-semester and one-quarter courses, as well as self-study, this self-contained text provides beginning students with the foundation they need to progress to more advanced study.

Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization.Security has become a "big data" problem. The growth rate of malw

This book introduces the concepts, applications and development of data science in the telecommunications industry by focusing on advanced machine learning and data mining methodologies in the wireles

This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform gener

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issue

This Level 1 guided reader series explores how road rollers are used on construction sites. Students will develop word recognition and reading skills while learning about exciting construction machine

近年來，機器學習領域受到越來越多的關注，相關的機器學習演算法開始成為熱點。 本書專門介紹了有關機器學習的內容，全書共分3部分：第1部分是資料科學和Microsoft Azure Machine Learning導論，介紹了資料科學和Microsoft Azure Machine Learning的基本知識以及需要用到的語言的基本知識；第二部分是統計學和機器學習演算法，系統地講解了統計學和機器學習的

This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search

本書探索了一系列廣泛應用的機器學習技術，用實際例子揭示了常見數據中隱藏的處理技巧和竅門。本書還探討了機器學習的前沿進展，提供了一些關於深度學習和強化學習的範例和指導原則，完美演繹了實操過程及算法原理。本書的目標讀者為那些想瞭解機器學習實踐通過機器學習技術解決現實應用的數據科學家。

Machine Learning Techniques for Space Weather provides a thorough and accessible presentation of machine learning techniques that can be employed by space weather professionals. Additionally, it prese

本書講解的是在R語言平臺上使用大數據技術構建可擴展機器學習模型的新技術成果。它全面展示了如何採用機器學習算法在原始數據的基礎上構建機器學習模型。本書還能讓那些希望利用ApacheHadoop、Hive、Pig和Spark來實現可擴展機器學習模型的讀者從中受益。

Machine learning and computerized data analysis is incredibly powerful, but humans still excel at "getting a sense of things"—the ability to recognize ill-defined or novel patterns or anomalies.

This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Ch

Originally developed to support video games, graphics processor units (GPUs) are now increasingly used for general-purpose (non-graphics) applications ranging from machine learning to mining of crypto

Accelerated Path to Cures provides a transformative perspective on the power of combining advanced computational technologies, modeling, bioinformatics and machine learning approaches with nonclinical

本書採用理論與實踐相結合的方式，在簡明扼要地闡明機器學習原理的基礎上，通過大量實例介紹了不同場景下機器學習算法在scikit-learn中的實現及應用。書中還有大量的代碼示例及圖例，便於讀者理解和學習並實際上手操作。另一方面，書中還有很多的延伸閱讀指導，方便讀者系統性地瞭解機器學習領域的現有技術及其發展狀態。

本書對機器學習的關鍵知識點進行了全面講解，幫助讀者順利完成從理論到實踐的過渡。書中首先介紹用於描述機器學習算法的統計與概率的知識，接著詳細分析機器學習技術的兩類主要方法――生成方法和判別方法，後深入研究了如何使機器學習算法在實際應用中發揮更大的作用。本書提供程序源代碼，便於讀者進行數據分析實踐。本書適合高等院校計算機、統計等專業的研究生和高年級本科生閱讀，同時也適合相關領域的技術人員參考。

A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges.The goal of data

Mixture analysis is very active research topic in statistics and machine learning. It is a good timing for a Handbook to present a broad overview of the methods and applications, suitable for graduate