Python data mining and machine learning in action

With the advent of the Al era, professionals need to select the right tools to meet new opportunities and challenges! This instructional material focuses on the application of big data analysis, text mining, and machine learning in auditing to assist readers in understanding the latest developments in data analysis and smart audit.JCAATs is a new generation audit software developed by Python, which can be executed in a Windows and MAC operation systems with a multi-language, visual, and easy-to-use interface. Non-IT professionals can easily conduct smart data analysis. Through JCAATs' built-in data fusion technology and OPEN DATA connector, heterogeneous data can be quickly analyzed in real-time and effectively identifying anomalies. The features of this book include:The book is structured to provide a progressive learning experience, with chapters covering different concepts and applications, as well as exercises and practice questions. The official textbook endorsed by ICAEA

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. Th

Machine learning allows computational systems to adaptively improve their performance with experience accumulated from the observed data. Its techniques are widely applied in engineering, science, fin

Practical Applications of Data Mining emphasizes both theory and applications of data mining algorithms. Various topics of data mining techniques are identified and described throughout, including clu

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, inc

This comprehensive volume presents the foundations of linear algebra ideas and techniques applied to data mining and related fields. Linear algebra has gained increasing importance in data mining and

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover

Python機器學習第三版（下） Python Machine Learning - Third Edition 第三版－最新修訂版，新增TensorFlow 2、GAN和強化學習等實用內容 使用Python的scikit-learn和TensorFlow 2融會貫通機器學習與深度學習 循序漸進、由淺入深，好評熱銷再進化！最新修訂的《Python機器學習第三版》是一本不容錯過的全方位指南，也是讀者

With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for ad

While most data mining algorithms deal with static data, the seven papers in this collection address systems producing massive high-speed streams of ever-changing data generated by dynamic process

Kantardzic (computer engineering and science, U. of Louisville) offers students a single-volume introduction to the methods, tools, and algorithms in data mining that can also be used as a broad, if s

This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts.

For courses in introductory statistics. The Art and Science of Learning from Data Statistics: The Art and Science of Learning from Data, Fourth Edition, takes a conceptual approach, helping students u

This volume investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. Such sequential investment strategies use information

This book is a customized version in Taiwan, and the content is extracted from Chapters 1 to 15 of the book "Introduction to Python Programming and Data Structures, Global Edition, 3rd edition".-- --For introductory courses in Python Programming.A fundamentals first approach to programming helps students create efficient, elegant code.Introduction to Python Programming and Data Structures introduces students to basic programming concepts using a fundamentals-first approach that prepares students to learn object-oriented programming and advanced Python programming. This approach presents programming concepts and techniques that include control statements, loops, functions, and arrays before designing custom classes. Students learn basic logic and programming concepts prior to moving into object-oriented and GUI programming. The content incorporates a wide variety of problems with various levels of difficulty and covers many application areas to engage and motivate students.For a list of

●NEW SECTION HIGHLIGHTS LEGAL AND ETHICAL ISSUES IN THE USE OF DATA AND ANALYTICS. Chapter 1 includes a new section that addresses common legal and ethical issues related to the use of data and analytics. This new legal and ethical section discusses recent data privacy laws as well as ethical issues that both practitioners and consumers of analytics models should consider.●PRACTICAL, RELEVANT PROBLEMS HELP STUDENTS MASTER CONCEPTS AND HANDS-ON SKILLS. Applications drawn from all functional business areas, including finance, marketing and operations, provide important practice at a variety of levels of difficulty. Time-saving data sets are available for most exercises and cases.●REVISED DATA MINING CHAPTERS OFFER CLEARER PRESENTATION OF CONCEPTS. The authors have reorganized and updated this edition's data mining chapters to ensure students thoroughly understand the presentation. The descriptive data mining chapter (Ch. 5) now appears after the probability chapter so that the data minin

Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, t

This book provides frequently studied and used machines together with soft computing methods such as evolutionary computation. The main topics of the machine learning cover Artificial Neural Networks

Deep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems

Deep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems

There is a lack of an exposition on interdisciplinary and innovative methods of data mining and visualization for biodata. This book fills the gap by introducing an interdisciplinary set of the most r

This book covers a wide range of subjects in applying machine learning approaches for bioinformatics projects. The book succeeds on two key unique features. First, it introduces the most widely used m

1. Added material on important techniques for data mining, including regression trees and neural network models in Chapters 11 and 13.2. The Chapter on logistic regression (Chapter 14) has been extens

Recent research in probability has been concerned with applications such as data mining and finance models. Some aspects of the foundations of probability theory have receded into the background. Yet,

Chapter 1: Introduction to Business IntelligenceChapter 2: Data WarehousingChapter 3: Business Performance ManagementChapter 4: Data Mining for Business IntelligenceChapter 5: Text and Web MiningChapt

For courses in Python ProgrammingIntroduces Python programming with an emphasis on problem-solvingNow in its Third Edition, Practice of Computing Using Python continues to introduce both majors and no

Data uncertainty widely exists in many applications, and an uncertain data stream is a series of uncertain tuples that arrive rapidly. However, traditional techniques for deterministic data streams ca

Data uncertainty widely exists in many applications, and an uncertain data stream is a series of uncertain tuples that arrive rapidly. However, traditional techniques for deterministic data streams ca

For college-level Computer Science courses in Python Basic Programming and Problem Solving in Python As one of the most widely used programming languages in the software industry, Python is desirable

Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning. They have found a great range of applications in various fields

This volume contains revised and extended research articles written by prominent researchers. Topics covered include electrical engineering, circuits, artificial intelligence, data mining, imaging eng

Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning. They have found a great range of applications in various fields

Elementary Linear Algebra: Applications Version, 12th Edition, gives an elementary treatment of linear algebra that is suitable for a first course for undergraduate students. The classic treatment of linear algebra presents the fundamentals in the clearest possible way, examining basic ideas by means of computational examples and geometrical interpretation. It proceeds from familiar concepts to the unfamiliar, from the concrete to the abstract. Readers consistently praise this outstanding text for its expository style and clarity of presentation. In this edition, a new section has been added to describe the applications of linear algebra in emerging fields such as data science, machine learning, climate science, geomatics, and biological modeling. New exercises have been added with special attention to the expanded early introduction to linear transformations and new examples have been added, where needed, to support the exercise sets. Calculus is not a prerequisite, but there are clea

Now in its 14th edition, Statistics for Business and Economics by McClave, Benson, and Sincich places statistics in the context of contemporary business. The text places emphasis on inference, extensively covering data collection and analysis needed to evaluate the results of statistical studies and make good decisions. Students are encouraged to develop statistical thinking and to understand both the assessment of credibility and the value of data inferences.Based on the American Statistical Association's Guidelines for Assessment and Instruction in Statistics Education(GAISE) Project, the text emphasizes statistical literacy, fosters active learning in the classroom, discusses intuitive probability, stresses conceptual understanding over mere knowledge of procedures, and employs technology to develop this understanding and to analyze data.

本書特色►萬物互聯，資料爆炸，物聯網時代，非邊緣運算不可►9大應用場景，5大核心技術，揭秘5G黑科技的邊緣運算專家推薦Explosion of connected devices and the tremendous amounts of data generated as a result of these devices and their machine-machine interactio

Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, GitHub, Instagram, and Google+? This new edition helps you discover who’s making connections with social media

This book is for teachers interested in incorporating interaction online into their teaching.Interaction Online is a valuable resource for anyone who wants to incorporate an aspect of online interaction in their language teaching. It is relevant for use with online, blended or face-to-face courses and appropriate for a wide range of teachers and learning contexts. This handbook contains over 75 tried and tested activities, the majority of which can be carried out either synchronously or asynchronously. Activities are purposeful and foster interaction between and among learners and instructors, rather than between learner and machine, and make use of generic tools and applications, such as discussion forums, instant message services and Facebook.

Are you keen to add Python to your programming skills? Learn quickly and have some fun at the same time withHead First Python. This updated book takes you beyond typical how-to manuals with engaging i

This book presents the recent achievements on the processing of representative user generated content (UGC) on E-commerce websites. This large size of UGC is valuable information for data mining to he

Gemstones Levels 22/23 Gold/SilverKey learning Area Social Studies and MathematicsTheme Gem Mining Title How Gemstones Are MinedText Type ExplanationPages 2–9Text Form Scientific WritingGenre Non-fict