Java | Data Science Made Easy
Richard M. Reese (u. a.)
Sold by preigu, Osnabrück, Germany
AbeBooks Seller since 5 August 2024
New - Soft cover
Condition: New
Ships from Germany to U.S.A.
Quantity: 5 available
Add to basketSold by preigu, Osnabrück, Germany
AbeBooks Seller since 5 August 2024
Condition: New
Quantity: 5 available
Add to basketJava | Data Science Made Easy | Richard M. Reese (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2017 | Packt Publishing | EAN 9781788475655 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Seller Inventory # 109477453
Data collection, processing, analysis, and more
This course is meant for Java developers who are comfortable developing applications in Java, and now want to enter the world of data science or wish to build intelligent applications. Aspiring data scientists with some understanding of the Java programming language will also find this book to be very helpful. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing your existing Java stack, this book is for you!
Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this course, we cover the basic as well as advanced data science concepts and how they are implemented using the popular Java tools and libraries.The course starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. You will examine the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. Throughout this course, the chapters will illustrate a challenging data science problem, and then go on to present a comprehensive, Java-based solution to tackle that problem. You will cover a wide range of topics - from classification and regression, to dimensionality reduction and clustering, deep learning and working with Big Data. Finally, you will see the different ways to deploy the model and evaluate it in production settings.
By the end of this course, you will be up and running with various facets of data science using Java, in no time at all.
This course contains premium content from two of our recently published popular titles:
This course follows a tutorial approach, providing examples of each of the concepts covered. With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.
"About this title" may belong to another edition of this title.
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