Statistical Methods For Data Science – alle Bücher

National Academies of Sciences Engineering and Medicine, Division on Engineering and Physical Sciences, National Materials and Manufacturing Board, Board on Mathematical Sciences and Analytics
Statistical and Data-Driven Methods for Additive Manufacturing Qualification

Additive manufacturing (AM), the process in which a three-dimensional (3D) object is built by adding subsequent layers of materials, enables novel material compositions and shapes, often without the need …

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Mathematical and Statistical Methods for Actuarial Sciences and Finance

The book presents a collection of peer-reviewed short papers selected from those presented at the International Conference Mathematical and Statistical Methods for Actuarial Sciences and Finance MAF2024…

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Andrea Bellavia
Statistical Methods for Environmental Mixtures

This book provides a comprehensive introduction to statistical approaches for the assessment of complex environmental exposures, such as pollutants and chemical mixtures, within the exposome framework. En…

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Practical Statistical Learning and Data Science Methods

This contributed volume offers practical implementation strategies for statistical learning and data science techniques, with fully peer-reviewed papers that embody insights and experiences gathered withi…

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Peter C Bruce, Peter Gedeck, Janet Dobbins
Statistics for Data Science and Analytics

Introductory statistics textbook with a focus on data science topics such as prediction, correlation, and data exploration Statistics for Data Science and Analytics is a comprehensive guide to statistical…

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Sustainable Statistical and Data Science Methods and Practices

This volume gathers papers presented at the LISA 2020 Sustainability Symposium in Kumasi, Ghana, May 2-6, 2022. They focus on sustainable methods and practices of using statistics and data science to addr…

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Carlos Fernandez-Granda
Probability and Statistics for Data Science

This accessible book for graduate students and data scientists provides a solid background in probabilistic and statistical concepts relevant to data science. Emphasis is placed on practice, with examples…

lieferbar ab 31.7.2025.

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Carlos Fernandez-Granda
Probability and Statistics for Data Science

This accessible book for graduate students and data scientists provides a solid background in probabilistic and statistical concepts relevant to data science. Emphasis is placed on practice, with examples…

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Steven E. Rigdon, Jr Ronald D. Fricker, Douglas C. Montgomery
Introduction to Probability and Statistics for Data Science

Introduction to Probability and Statistics for Data Science provides a solid course in the fundamental concepts, methods and theory of statistics for students in statistics, data science, biostatistics, e…

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Grey Ballard, Tamara G. Kolda
Tensor Decompositions for Data Science

Aimed at students in mathematics, computer science, statistics, engineering, and physical and life sciences, this book introduces the foundations of tensor decompositions, a data analysis methodology ubiq…

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Machine Learning for Data Science Handbook

This book is a major update to the very successful first and second editions (2005 and 2010) of Data Mining and Knowledge Discovery Handbook. Since the last edition, this field has continued to evolve and…

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Fedor
Cleaning Up Your Act: Statistical Methods for Detecting Outliers in Regression

"Cleaning Up Your Act: Statistical Methods for Detecting Outliers in Regression" dives into the world of data analysis, specifically focusing on a crucial step: identifying outliers in regression models. …

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Alex Ruiz de Villa
Causal Inference for Data Science

Causal Inference for Data Science introduces data-centric techniques and methodologies you can use to estimate causal effects. The numerous insightful examples show you how to put causal inference into pr…

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Allon Adir, Ehud Aharoni, Omri Soceanu, Ronen Levy
Homomorphic Encryption for Data Science (HE4DS)

This book provides basic knowledge required by an application developer to understand and use the Fully Homomorphic Encryption (FHE) technology for privacy preserving Data-Science applications. The author…

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Vidya Subramanian
Applied Machine Learning for Data Science Practitioners

Applied Machine Learning for Data Science Practitioners Vidya Subramanian A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning…

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Jeffrey A. Fessler, Raj Rao Nadakuditi
Linear Algebra for Data Science, Machine Learning, and Signal Processing

"Master basic matrix methods by seeing how the math is used in practice in a range of data-driven applications. Includes a wealth of engaging exercises for quizzes, self-study and interactive learning, as…

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Advanced Methods in Statistics, Data Science and Related Applications

This book contains a selection of the improved contributions submitted by participants at the conference of the Italian Statistical Society - SIS 2022 held in Caserta 22-24 June 2022. The scientific commu…

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Michael Hagmann, Stefan Riezler
Validity, Reliability, and Significance

This book introduces empirical methods for machine learning with a special focus on applications in natural language processing (NLP) and data science. The authors present problems of validity, reliabilit…

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The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences

"The first of three volumes, the five parts of this book cover a variety of issues important in developing, designing, and analyzing data to produce high-quality research efforts and cultivate a productiv…

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The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences: Volume 2

"The first of three volumes, the five parts of this book cover a variety of issues important in developing, designing, and analyzing data to produce high-quality research efforts and cultivate a productiv…

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