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English | ISBN: 1119327636 | 2017 | EPUB | 384 Pages | 10,3 MB Your ticket to breaking into the field of data science! Jobs in data science are projected to outpace the number of people with data science skills-making those with the knowledge to fill a data science position a hot commodity in the coming years. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of an organization's massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It's a big, big data world out there-let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

English | ISBN: 1786460181 | 2017 | EPUB | 508 Pages | 7,4 MB Key Features Master the searching, indexing, and aggregation features in ElasticSearch Improve users' search experience with Elasticsearch's functionalities and develop your own Elasticsearch plugins A comprehensive, step-by-step guide to master the intricacies of ElasticSearch with ease Book Description Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. Elasticsearch leverages the capabilities of Apache Lucene, and provides a new level of control over how you can index and search even huge sets of data. With this book you will finally be able to fully utilize the power that Elasticsearch. We will start with a brief recap on the basics and also introduce you to the new features of Elasticsearch 5.0. We will guide you through the intermediate and advanced functionalities of Elasticsearchsuch as querying, indexing, searching, and modifying data. We'll also explore advanced concepts including aggregation, index control, sharding, replication, and clustering. We'll show you the modules of monitoring and administration available in Elasticsearch, and will also cover backup and recovery. You will get an understanding of how you can scale your ElasticSearch cluster to contextualize it and improve its performance. We'll also show you how you can create your own analysis plugin in Elasticsearch. By the end of the book, you will have all the knowledge necessary to master Elasticsearch and put it to efficient use. What you will learn Understand Apache Lucene and the Elasticsearch 5.0 design and architecture Use and configure the new and improved default text scoring mechanism in Apache Lucene 6 Know how to overcome the pitfalls while handling relational data in Elasticsearch Write and develop customized plugins to extend Elasticsearch Explore the right way of scaling production clusters to improve the performance of Elasticsearch

Quickly learn how to automate unit testing of Python 3 code with Python 3 automation libraries, such as doctest, unittest, nose, nose2, and pytest. This book explores the important concepts in software testing and their implementation in Python 3 and shows you how to automate, organize, and execute unit tests for this language. This knowledge is often acquired by reading source code, manuals, and posting questions on community forums, which tends to be a slow and painful process. Python Unit Test Automation will allow you to quickly ramp up your understanding of unit test libraries for Python 3 through the practical use of code examples and exercises. All of which makes this book a great resource for software developers and testers who want to get started with unit test automation in Python 3 and compare the differences with Python 2. This short work is your must-have quick start guide to mastering the essential concepts of software testing in Python.