Data science and analysis
Explore the dynamic field of data science and analysis, where statistical techniques and computational tools come together to uncover insights from vast datasets. This category offers a range of resources tailored for students, professionals, and anyone looking to enhance their data literacy, including definitive texts on algorithms, machine learning, and data visualization. Dive into the evolving landscape of this essential discipline and discover how data shapes decision-making across various industries.
Business Skills for Data Scientists: Practical Guidance in Six Key Topics
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The Science of Science: Big Data, Metrics, and Impact
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Tidy Modeling with R: A Framework for Modeling in the Tidyverse
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Python in a Nutshell: A Desktop Quick Reference
Alex Martelli, Steve Holden, Anna Ravenscroft, Paul Mcguire
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Confident Data Science: Discover the Essential Skills of Data Science
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HTML and CSS: The Comprehensive Guide
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Artificial Intelligence for Business: Harness AI for Value, Growth and Innovation
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Mindmasters: The Data-Driven Science of Predicting and Changing Human Behavior
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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)
Joe Hair, Marko Sarstedt, Christian M. M. Ringle, G. Tomas M. Tomas M. Hult
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Data Excellence: How Data Leadership Can Drive Stronger Organizational Performance
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The 14th Conference on Information Technology and its Applications: Proceedings of the International Conference CITA 2025
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Dont Trust Your Gut: Using Data Instead of Instinct to Make Better Choices
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The Definitive Guide to Power Query (M): Mastering complex data transformation with Power Query
Melissa de Korte, Gregory Deckler, Rick de Groot
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Introduction to Error Control Codes
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COMPUTATIONAL BIOLOGY&GENOME INFORMATICS
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Organizational Data Mining: Leveraging Enterprise Data Resources for Optimal Performance
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Towards Zero Downtime: High Availability Blueprints
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60 hot to touch Accessible Web Design tips - the tips no web developer can live without!
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Interactive Information Retrieval in Digital Environments
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Multimedia Transcoding in Mobile and Wireless Networks
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Model Induction from Data: Towards the Next Generation of Computational Engines in Hydraulics and Hydrology
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DITA 101
Steve Manning, Charles Cooper, Ann Rockley
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Pentaho 3.2 Data Integration: Beginners Guide
Maria Carina Roldan, Maria Carina Roldn
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The Complete Guide to I.T. Service Level Agreements: Aligning It Services to Business Needs
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Oracle Goldengate 11g Implementers Guide
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Pentaho Data Integration 4 Cookbook
Mar A. Carina Rold N., Adri N. Sergio Pulvirenti, Adrian Sergio Pulvirenti
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Multilevel Models: Applications using SAS®
Jichuan Wang, James F. Fisher, Haiyi Xie
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Category „Data science and analysis“
Data science and analysis encompasses a vital and rapidly evolving field that combines statistics, computer science, and domain expertise to extract meaningful insights from diverse data sets. As industries increasingly rely on data-driven decision-making, this category serves as an invaluable resource for professionals, students, and enthusiasts alike who seek to navigate the complexities of modern data landscapes.
The origins of data science trace back to the advent of computing and statistics, developing into a distinct discipline over the years. Today, it plays a crucial role in various sectors, from business analytics and healthcare to academia and government. Readers engaged in this field can expect to find a collection of insightful texts that cover fundamental concepts, advanced methodologies, and practical applications of data analysis.
Diving into data science not only enriches one's analytical skills but also enhances problem-solving capabilities across a multitude of contexts. Those exploring this category will find works that tackle essential themes such as data visualization, machine learning techniques, and statistical analysis, providing a comprehensive understanding of how to interpret and leverage data effectively.
This category features a diverse array of authors and publishers, including prominent thought leaders and established experts in the field. Their contributions reflect the latest trends and research, making this an up-to-date and relevant resource for anyone looking to deepen their knowledge and skillset in data science and analysis.