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Updated to emphasize new features in Spark 2.4., this second edition shows data engineers and scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine-learning algorithms.
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning.... Læs mere
Presents the commonly needed techniques for working with population statistics, irrespective of the reader's mathematical background. This book provides concepts and... Læs mere
Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles.
Work with petabyte-scale datasets while building a collaborative, agile workplace in the process. This practical book is the canonical reference to Google BigQuery, the query engine that lets you conduct interactive analysis of large datasets.
Manage your data with a system designed to support modern application development. Updated for MongoDB 4.2, the third edition of this authoritative and accessible guide shows you the advantages of using document-oriented databases.
Intermediate-Advanced user level
This guide will help the reader to learn the key features constructively and get more out of Access.
Getting numbers is easy; getting trustworthy numbers is hard. From experimentation leaders at Amazon, Google, LinkedIn, and... Læs mere