Dakota Forest – Bücher, CDs, LPs und mehr, Seite 6

Ralf Kneuper
Data Protection for Software Development and IT

This book introduces data protection, i.e. the protection of individuals from misuse of their personal data. It provides a special focus on the direct impact on software development, e.g. in the form of f…

lieferbar innerhalb 2-3 Wochen

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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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Vidya Subramanian
Applied Machine Learning for Data Science Practitioners

A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML).Applied Machine Learning for Data Science Practitioners offers a pract…

lieferbar in mind. 4 Wochen

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Multimodal and Tensor Data Analytics for Industrial Systems Improvement

This volume covers the latest methodologies for using multimodal data fusion and analytics across several applications. The curated content presents recent developments and challenges in multimodal data a…

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Byron J. T. Morgan, Emily B. Dennis, Stephen T. Buckland
Statistical Models for Wildlife Survey Data

This book describes a range of models for ecological data sets using both classical and Bayesian methods of inference, and illustrates their use through a varied set of real examples. These examples exhib…

lieferbar ab 12.5.2026.

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Ryan Day
Hands-On APIs for AI and Data Science

Are you ready to grow your skills in AI and data science? A great place to start is learning to build and use APIs in real-world data and AI projects. API skills have become essential for AI and data scie…

sofort lieferbar

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Raphael Röttinger
Data Analysis and Risk Modelling for Terrorism Prevention:

In the field of terrorism prevention, data analysis plays a critical role in developing predictive models to address the growing complexity of modern terrorist tactics. This book examines the challenges, …

sofort lieferbar

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Michael Roberts
The Data Book for Educators Who Don't Like Data (and Those Who Want to Use Data Better)

Data is one of the most powerful guides to instructional efficacy, revealing insights about the students you serve. Author Michael Roberts challenges educators to move past correlative data to active, dat…

lieferbar ab 6.3.2026.

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Handbook of Artificial Intelligence and Data Sciences for Routing Problems

This handbook delves into the rapidly evolving field of artificial intelligence and optimization, focusing on the intersection of machine learning, combinatorial optimization, and real-world applications …

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AI and Data Analytics in Precision Agriculture for Sustainable Development

This book offers a comprehensive analysis of artificial intelligence (AI) and data analytics in precision agriculture. The integration of technology in agriculture is revolutionizing traditional farming p…

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Data Science, Classification, and Artificial Intelligence for Modeling Decision Making

This book gathers selected and peer-reviewed contributions presented at the 18th Conference of the International Federation of Classification Societies (IFCS 2024), held in San José, Costa Rica, July 15--…

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Joachim Hunker
Method for Combining Data Farming and Data Mining in a Logistics Assistance System for Materials Trading Networks Based on Graph Databases

To maintain the competitiveness of a materials trading network, decision-makers are confronted with a multitude of logistics tasks. Finding answers to these tasks often involves a decision-making process,…

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Ma Nang Laik, Michelle L. F. Cheong
Data and Decision Analytics for Business Operations

In this book, readers will be exposed to the Data and Decision Analytics Framework which helps a business analyst to first identify the root cause of business problems by collecting, preparing, and explor…

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Age K Smilde, Federico Marini, Johan A Westerhuis, Kristian Hovde Liland
Analysis of Variance for High-Dimensional Data

Overview of methods for analyzing high-dimensional experimental data, including theory, methodologies, and applicationsAnalysis of Variance for High-Dimensional Data summarizes all the methods to analyze …

lieferbar in mind. 4 Wochen

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Nature-Inspired Methods for Smart Healthcare Systems and Medical Data

This book aims to gather high-quality research papers on developing theories, frameworks, architectures, and algorithms for solving complex challenges in smart healthcare applications for real industry us…

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Shirui Wang, Jiefu Chen, Xuqing Wu, Wenyi Hu
Deep Learning for Seismic Data Enhancement and Representation

Seismic imaging is a key component of subsurface exploration, and it depends on a high-quality seismic data acquisition system with effective seismic processing algorithms. Seismic data quality concerns v…

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Andrei P. Kirilenko
Practical Data Mining with AI for Social Scientists

This book is designed as a foundational textbook for upper-level undergraduate and graduate students from non-technical fields who want to acquire a basic understanding of data science and learn practical…

lieferbar ab 9.12.2025.

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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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Next Generation Data Science and Blockchain Technology for Industry 5.0

A groundbreaking view of the industrial models of the futureIndustry 5.0 is an increasingly widespread term for the coming business paradigm, which will combine humans, robotics, and smart technology to c…

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Ramesh S. V. Teegavarapu
Imputation Methods for Missing Hydrometeorological Data Estimation

Missing data is a ubiquitous problem that plagues many hydrometeorological datasets. Objective and robust spatial and temporal imputation methods are needed to estimate missing data and create error-free,…

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