Data science and analysis: general

This fully revised and updated edition of the bestselling Chief Data Officer's Playbook offers new insights into the role of the CDO and the data environment.

Organize, plan, and build an exceptional data analytics team within your organization In Minding the Machines: Building and Leading Data Science and Analytics Teams, AI and analytics strategy expert Jeremy Adamson delivers an accessible and insightful roadmap to structuring and leading a successful analytics team.

Data Alchemy in the Insurance Industry: The Transformative Power of Big Data Analytics is a groundbreaking work that explores the transformative power of big data analytics within the insurance industry.

Jump-start your career as a data scientist learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most.

Presents numerical methods for reservoir simulation, with efficient implementation and examples using widely-used online open-source code, for researchers, professionals and advanced students.

Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope.

Displays the broad range of quantitative approaches to analysing ecological networks, providing clear examples and guidance for researchers.

Single system, or single case, design studies are a convenient method for evaluating practice, allowing professionals to track clients' response to treatment and change over time.

An intuitive, up-to-date introduction to random matrix theory and free calculus, with real world illustrations and Big Data applications.

How can HR professionals utilize and leverage their organization's data effectively, with the use of AI, for more talent attraction, better employee engagement and higher talent retention to ultimately drive performance?

This is a book about how ecologists can integrate remote sensing and GIS in their daily work.

Presents the methodology of big data analysis using examples from research and industry There are large amounts of data everywhere, and the ability to pick out crucial information is increasingly important.

From Social Science to Data Science is a fundamental guide to scaling up and advancing your programming skills in Python.

Recent data shows that 87% of Artificial Intelligence/Big Data projects don't make it into production (VB Staff, 2019), meaning that most projects are never deployed.

Who is most likely to buy and what is the best way to target them?

Many librarians' job responsibilities increasingly require them to understand and handle data.

This is a book about the scientific process and how you apply it to data in ecology.

Many businesses are based on creating desirable experiences, products and services for users.

Organize, plan, and build an exceptional data analytics team within your organization In Minding the Machines: Building and Leading Data Science and Analytics Teams, AI and analytics strategy expert Jeremy Adamson delivers an accessible and insightful roadmap to structuring and leading a successful analytics team.

From measles to COVID, discover how data allied with statistical and probabilistic reasoning are essential to making rational decisions.

This fully revised and updated edition of the bestselling Chief Data Officer's Playbook offers new insights into the role of the CDO and the data environment.

A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "e;language"e; of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods.

A fascinating exploration of how algorithms penetrate the most intimate aspects of our psychologyfrom the pioneering expert on psychological targeting.

This is an integrated introduction to methods, research design, and data analysis tailored to the challenges of cross-cultural research.

Summary The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source.

Este libro es la guía definitiva para dominar Excel y Power BI, dos de las herramientas más poderosas en el mundo del análisis y visualización de datos.

A concise, systematic introduction to the principles of analysis of variance for post-graduates and professionals.

Focus on Geodatabases in ArcGIS Pro introduces readers to the geodatabase, the comprehensive information model for representing and managing geographic information across the ArcGIS platform.

Employs basic mathematical skills to teach students how to address topical, real-world problems using quantitative reasoning.

A comprehensive introduction and teaching resource for state-of-the-art Qualitative Comparative Analysis (QCA) using R software.

A comprehensive guide to data analysis techniques for the physical sciences including probability, statistics, data reconstruction, data correction and Monte Carlo methods.

Don't simply show your data tell a story with it!

Practical guide for deriving insight and commercial gain from data Monetising Data offers a practical guide for anyone working with commercial data but lacking deep knowledge of statistics or data mining.

Este libro es una guia completa para cualquier persona que desee sumergirse en la programacion de computadoras, independientemente del area o disciplina del conocimiento.

A methodological toolkit for social scientists to create their own infrastructure for collecting and analyzing social media big data.