Test Data Engineering, Shojima

Автор: Strang Gilbert
Название: Linear Algebra and Learning from Data
ISBN: 0692196382 ISBN-13(EAN): 9780692196380
Издательство: Cambridge Academ
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Цена: 9978.00 р.
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Описание: 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, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Автор: Currell Graham
Название: Scientific Data Analysis
ISBN: 0198712545 ISBN-13(EAN): 9780198712541
Издательство: Oxford Academ
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Цена: 7602.00 р.
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Описание: Drawing on the author`s extensive experience of supporting students undertaking projects, Scientific Data Analysis is a guide for any science undergraduate or beginning graduate who needs to analyse their own data, and wants a clear, step-by-step description of how to carry out their analysis in a robust, error-free way.

Автор: Guerrero, Hector
Название: Excel data analysis
ISBN: 3030012786 ISBN-13(EAN): 9783030012786
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book offers a comprehensive and readable introduction to modern business and data analytics.

Автор: Leskovec Jure
Название: Mining of Massive Datasets
ISBN: 1108476341 ISBN-13(EAN): 9781108476348
Издательство: Cambridge Academ
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Цена: 10771.00 р.
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Описание: Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

Автор: Timbers, Tiffany-anne (university Of British Colum
Название: Data science
ISBN: 0367524686 ISBN-13(EAN): 9780367524685
Издательство: Taylor&Francis
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Цена: 7501.00 р.
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Описание: Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and cleaning, create effective visualizations, and extract insights from data using supervised predictive models.

Автор: Baltagi Badi H.
Название: Econometric Analysis of Panel Data
ISBN: 3030539520 ISBN-13(EAN): 9783030539528
Издательство: Springer
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Цена: 9083.00 р.
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Описание: Introduction.- The One-Way Error Component Regression Model.- The Two-Way Error Component Regression Model.- Test of Hypotheses with Panel Data.- Heteroskedasticity and Serial Correlation in the Error Component Model.- Seemingly Unrelated Regressions with Error Components.- Simultaneous Equations with Error Components.- Dynamic Panel Data Models.- Unbalanced Panel Data Models.- Special Topics.- Limited Dependent Variables and Panel Data.- Nonstationary Panels.- Spatial Panel Data Models.

Автор: Tor Lattimore, Csaba Szepesvari
Название: Bandit Algorithms
ISBN: 1108486827 ISBN-13(EAN): 9781108486828
Издательство: Cambridge Academ
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Цена: 6970.00 р.
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Описание: Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is an excellent reference for established researchers and a resource for graduate students interested in exploring stochastic, adversarial and Bayesian frameworks.

Автор: Kavita Taneja, Harmunish Taneja
Название: Data science and innovations for intelligent systems :
ISBN: 0367676273 ISBN-13(EAN): 9780367676278
Издательство: Taylor&Francis
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Цена: 22202.00 р.
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Описание: This book not only focuses on the practical applications of data science to achieve computational excellence, but also digs deep into the issues and implications of intelligent systems.

Автор: Gaciu Nicoleta
Название: Understanding Quantitative Data in Educational Research
ISBN: 1473982146 ISBN-13(EAN): 9781473982147
Издательство: Sage Publications
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Цена: 16632.00 р.
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Описание: This book is designed to help Education students gain confidence in analysing and interpreting quantitative data and using appropriate statistical tests, by exploring, in plain language, a variety of data analysis methods.

Автор: Treiman Donald J
Название: Quantitative Data Analysis
ISBN: 0470380039 ISBN-13(EAN): 9780470380031
Издательство: Wiley
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Цена: 11714.00 р.
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Описание: This book is an accessible introduction to quantitative data analysis, concentrating on the key issues facing those new to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results.

Автор: Michael C. Whitlock, Dolph Schluter
Название: The Analysis of Biological Data
ISBN: 1319325343 ISBN-13(EAN): 9781319325343
Издательство: Macmillan Learning
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Цена: 13858.00 р.
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Описание: The evolution of a classicThe new 12th edition of Introduction to Genetic Analysis takes this cornerstone textbook to the next level.