learning from data - 三民網路書店

79折

Machine Learners ─ Archaeology of a Data Practice

作者：Adrian Mackenzie 出版社：Mit Pr 出版日：2017/11/16 裝訂：精裝

Machine learning -- programming computers to learn from data -- has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transactio

定價：2200 元，優惠價：79 1738

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Statistical Inference for Engineers and Data Scientists

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142.

Statistical Inference for Engineers and Data Scientists

作者：Pierre Moulin 出版社：Cambridge Univ Pr 出版日：2018/12/31 裝訂：精裝

This book is a mathematically accessible and up-to-date introduction to the tools needed to address modern inference problems in engineering and data science, ideal for graduate students taking courses on statistical inference and detection and estimation, and an invaluable reference for researchers and professionals. With a wealth of illustrations and examples to explain the key features of the theory and to connect with real-world applications, additional material to explore more advanced concepts, and numerous end-of-chapter problems to test the reader's knowledge, this textbook is the 'go-to' guide for learning about the core principles of statistical inference and its application in engineering and data science. The password-protected solutions manual and the image gallery from the book are available online.

定價：3639 元，優惠價：9 3275

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143.

Data Mining And Statistics For Decision Making

作者：Tufféry 出版社：John Wiley & Sons Inc 出版日：2011/03/11 裝訂：精裝

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the i

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Analysis of Multivariate and High-Dimensional Data

90折

144.

Analysis of Multivariate and High-Dimensional Data

作者：Inge Koch 出版社：Cambridge Univ Pr 出版日：2013/12/31 裝訂：精裝

'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduat

定價：3899 元，優惠價：9 3509

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Cognitive Computing And Big Data Analytics

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145.

Cognitive Computing And Big Data Analytics

作者：Hurwitz 出版社：John Wiley & Sons Inc 出版日：2015/02/20 裝訂：平裝

A comprehensive guide to learning technologies that unlock the value in big dataCognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and der

定價：2250 元，優惠價：9 2025

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146.

Workshop Statistics: Discovery With Data, Fourth Edition

作者：Rossman 出版社：John Wiley & Sons Inc 出版日：2011/10/07 裝訂：平裝

Allan Rossman's 4th Edition of Workshop Statistics: Discovery with Data, is enhanced from previous issues with more focus and emphasis on collaborative learning. It further requires student observatio

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147.

Workshop Statistics: Discovery With Data, Fourth Edition

作者：Rossman 出版社：John Wiley & Sons Inc 出版日：2011/10/07 裝訂：精裝

Allan Rossman's 4th Edition of Workshop Statistics: Discovery with Data, is enhanced from previous issues with more focus and emphasis on collaborative learning. It further requires student observatio

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Contexts of Learning Mathematics and Science ─ Lessons Learned from TIMSS

90折

148.

Contexts of Learning Mathematics and Science ─ Lessons Learned from TIMSS

作者：Sarah J. Howie (EDT); Tjeerd Plomp (EDT) 出版社：Taylor & Francis 出版日：2008/05/23 裝訂：平裝

This book is the result of research from over fifteen countries, asking which background and environmental factors influence achievement in mathematics and science. This research is based on data from

定價：2473 元，優惠價：9 2226

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149.

Statistical Regression and Classification ─ From Linear Models to Machine Learning

作者：Norman Matloff 出版社：Chapman & Hall 出版日：2017/06/28 裝訂：平裝

This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned into a main body section and an "extras" section. The main bod

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150.

American Salaries and Wages Survey ─ Statistical Data Derived from More Than 340 Government, Business & News Sources

作者：Gale Cengage Learning (COR) 出版社：Gale ; Cengage Learning 出版日：2017/06/02 裝訂：精裝

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Data Analysis With Microsoft Access 2010 ─ From Simple Queries to Business Intelligence

90折

151.

Data Analysis With Microsoft Access 2010 ─ From Simple Queries to Business Intelligence

作者：Larry Rockoff 出版社：Cengage Learning 出版日：2011/10/28 裝訂：平裝

DATA ANALYSIS WITH MICROSOFT ACCESS 2010 is an introduction to Access with an emphasis on topics relevant to data analysis. The goal is to help the analyst gain a true understanding of data and the in

定價：1260 元，優惠價：9 1134

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152.

Machine Intelligence: Demystifying Machine Learning, Neural Networks and Deep Learning

作者：Suresh Samudrala 出版社：Independently published 出版日：2019/01/11 裝訂：平裝

Artificial intelligence and machine learning are considered as hot technologies of this century. As these technologies move from research labs to enterprise data centers, the need for skilled professi

定價：945 元，優惠價：1 945

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153.

Motivational Dynamics in Language Learning

作者：Zoltan Dornyei; Alastair Henry 出版社：Utp Distribution 出版日：2014/10/15 裝訂：精裝

This landmark volume offers a collection of conceptual papers and data-based research studies that investigate the dynamics of language learning motivation from a complex dynamic systems perspective.

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154.

Young People, Learning and Storytelling

作者：Emma Parfitt 出版社：Palgrave Macmillan 出版日：2018/11/28 裝訂：精裝

This book explores the lives of young people through the lens of storytelling. Using extensive qualitative and empirical data from young people’s conversations following storytelling performances in s

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155.

Smart Learning in Smart Cities

作者：Dejian Liu; Ronghuai Huang; Marek Wosinski 出版社：Springer Verlag 出版日：2017/04/14 裝訂：精裝

This book introduces readers to the current status of smart learning in China by providing extensive and accurate data from different contexts of smart learning. In particular, it investigates smart l

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156.

Mathematical Aspects of Deep Learning

作者：Philipp Grohs 出版社：Cambridge Univ Pr 出版日：2022/10/31 裝訂：精裝

In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics. This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves as both a starting point for researchers and graduate students in mathematics trying to get into the field, as well as an invaluable reference for future research.

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滿額折

157.

Motivational Dynamics in Language Learning

作者：Zoltan Dornyei; Alastair Henry 出版社：Multilingual Matters Ltd 出版日：2014/10/15 裝訂：平裝

This landmark volume offers a collection of conceptual papers and data-based research studies that investigate the dynamics of language learning motivation from a complex dynamic systems perspective.

定價：2097 元，優惠價：95 1992

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90折

158.

Bayesian Reasoning and Machine Learning

作者：David Barber 出版社：Cambridge Univ Pr 出版日：2011/12/31 裝訂：精裝

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors,

定價：3964 元，優惠價：9 3568

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159.

Learning Scientific Programming With Python

作者：Christian Hill 出版社：Cambridge Univ Pr 出版日：2016/02/29 裝訂：精裝

Learn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targe

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160.

Unsupervised Learning: A Dynamic Approach

作者：Kyan 出版社：John Wiley & Sons Inc 出版日：2014/05/23 裝訂：精裝

To aid in intelligent data mining, this book introduces a new family of unsupervised algorithms that have a basis in self-organization, yet are free from many of the constraints typical of other well

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Machine Learners ─ Archaeology of a Data Practice

Statistical Inference for Engineers and Data Scientists

Data Mining And Statistics For Decision Making

Analysis of Multivariate and High-Dimensional Data

Cognitive Computing And Big Data Analytics

Workshop Statistics: Discovery With Data, Fourth Edition

Workshop Statistics: Discovery With Data, Fourth Edition

Contexts of Learning Mathematics and Science ─ Lessons Learned from TIMSS

Statistical Regression and Classification ─ From Linear Models to Machine Learning

American Salaries and Wages Survey ─ Statistical Data Derived from More Than 340 Government, Business & News Sources

Data Analysis With Microsoft Access 2010 ─ From Simple Queries to Business Intelligence

Machine Intelligence: Demystifying Machine Learning, Neural Networks and Deep Learning

Motivational Dynamics in Language Learning

Young People, Learning and Storytelling

Smart Learning in Smart Cities

Mathematical Aspects of Deep Learning

Motivational Dynamics in Language Learning

Bayesian Reasoning and Machine Learning

Learning Scientific Programming With Python

Unsupervised Learning: A Dynamic Approach