Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes),
Автор: Luckey Название: Membrane Structural Biology ISBN: 1107030633 ISBN-13(EAN): 9781107030633 Издательство: Cambridge Academ Рейтинг: Цена: 62310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This textbook provides a strong foundation and comprehensive overview for students and an invaluable synthesis of cutting-edge research for working scientists. This second edition is expanded to include and make accessible all the latest developments and topics, with more than twenty new high resolution structures. Links between membrane research and human health are emphasised throughout.
Автор: Wolfgang Karl H?rdle; Henry Horng-Shing Lu; Xiaoto Название: Handbook of Big Data Analytics ISBN: 3319182838 ISBN-13(EAN): 9783319182834 Издательство: Springer Рейтинг: Цена: 260870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Автор: Guida Название: Big Data and Machine Learning in Quantitative Investment ISBN: 1119522196 ISBN-13(EAN): 9781119522195 Издательство: Wiley Рейтинг: Цена: 44350.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Get to know the 'why' and 'how' of machine learning and big data in quantitative investment
Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it's a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance.
The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning.
- Gain a solid reason to use machine learning
- Frame your question using financial markets laws
- Know your data
- Understand how machine learning is becoming ever more sophisticated
Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment -- and this book shows you how.
Автор: Ivezic?, Z?eljko, Название: Statistics, data mining, and machine learning in astronomy : ISBN: 0691198306 ISBN-13(EAN): 9780691198309 Издательство: Wiley Рейтинг: Цена: 82370.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, engage with the different methods, and adapt them to their own fields of interest.
An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.
Fully revised and expanded
Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets
Features real-world data sets from astronomical surveys
Uses a freely available Python codebase throughout
Ideal for graduate students, advanced undergraduates, and working astronomers
Автор: Witten, Ian H. Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed. ISBN: 0128042915 ISBN-13(EAN): 9780128042915 Издательство: Elsevier Science Рейтинг: Цена: 61750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Samantha Kleinberg Название: Time and Causality Across the Sciences ISBN: 1108476678 ISBN-13(EAN): 9781108476676 Издательство: Cambridge Academ Рейтинг: Цена: 61240.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides an entry point for researchers in any field, bringing together perspectives collected from a large body of work on causality across disciplines. Topics include whether quantum mechanics allows causes to precede their effects, the integration of mechanisms, and insight into the role played by intervention and timing information.
Автор: Airyalat Название: A Beginner`s Guide to Using Open Access Data ISBN: 0367075032 ISBN-13(EAN): 9780367075033 Издательство: Taylor&Francis Рейтинг: Цена: 22450.00 T Наличие на складе: Нет в наличии. Описание: Open Access Data is emerging as a source for cutting edge scholarship. This concise book provides guidance from generating a research idea to publishing results. Both young researchers and well-established scholars can use this book to upgrade their skills with respect to emerging data sources, analysis, and even post-publishing promotion.
Автор: Menczer Filippo Название: First Course in Network Science ISBN: 1108471137 ISBN-13(EAN): 9781108471138 Издательство: Cambridge Academ Рейтинг: Цена: 43290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A practical introduction to network science suitable for students studying diverse programs such as business, cognitive science, neuroscience, sociology, biology, and engineering. A wide range of examples and exercises develop readers` understanding, and Python programming tutorials provided online reinforce coding skills.
Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges.You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things.
What You'll Learn
Gain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AISelect learning methods/algorithms and tuning for use in healthcareRecognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agents
Who This Book Is For
Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.
Автор: Steven L. Brunton, J. Nathan Kutz Название: Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control ISBN: 1108422098 ISBN-13(EAN): 9781108422093 Издательство: Amazon Internet Рейтинг: Цена: 0.00 T Наличие на складе: Невозможна поставка. Описание: Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. Aimed at advanced undergraduate and beginning graduate students, this textbook provides an integrated viewpoint that shows how to apply emerging methods from data science, data mining, and machine learning to engineering and the physical sciences.
Автор: Robert Nisbet , Gary Miner, Ken Yale Название: Handbook of Statistical Analysis and Data Mining Applications, 2 ed. ISBN: 0124166326 ISBN-13(EAN): 9780124166325 Издательство: Elsevier Science Рейтинг: Цена: 88690.00 T Наличие на складе: Поставка под заказ. Описание:
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application.
This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas--from science and engineering, to medicine, academia and commerce.
Includes input by practitioners for practitioners
Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models
Contains practical advice from successful real-world implementations
Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions
Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Автор: McCallum Q Ethan Название: Bad Data Handbook ISBN: 1449321887 ISBN-13(EAN): 9781449321888 Издательство: Wiley Рейтинг: Цена: 33780.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Welcome to data science`s dirty secret: real-world data is messy. Data scientists must spend a good deal of time playing software developer, writing code to clean up data before they can actually do anything constructive with it. This is a necessary evil, but we can still make the most of it.
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