Author: Rushdi Shams Full Title: Java Data Science Cookbook Publisher: Packt Publishing - ebooks Account (March 28, 2017) Year: 2017 ISBN-13: 9781787122536 (978-1-78712-253-6) ISBN-10: 1787122530 Pages: 372 Language: English Genre: Programming File type: PDF (True, but nonnative Cover) Quality: 9/10 Price: $49.99 Recipes to help you overcome your data science hurdles using Java. If you are looking to build data science models that are good for production, Java has come to the rescue. With the aid of strong libraries such as MLlib, Weka, DL4j, and more, you can efficiently perform all the data science tasks you need to. This unique book provides modern recipes to solve your common and not-so-common data science-related problems. We start with recipes to help you obtain, clean, index, and search data. Then you will learn a variety of techniques to analyze, learn from, and retrieve information from data. You will also understand how to handle big data, learn deeply from data, and visualize data. Finally, you will work through unique recipes that solve your problems while taking data science to production, writing distributed data science applications, and much more—things that will come in handy at work. What You Will Learn: — Find out how to clean and make datasets ready so you can acquire actual insights by removing noise and outliers — Develop the skills to use modern machine learning techniques to retrieve information and transform data to knowledge. retrieve information from large amount of data in text format. — Familiarize yourself with cutting-edge techniques to store and search large volumes of data and retrieve information from large amounts of data in text format — Develop basic skills to apply big data and deep learning technologies on large volumes of data — Evolve your data visualization skills and gain valuable insights from your data — Get to know a step-by-step formula to develop an industry-standard, large-scale, real-life data product — Gain the skills to visualize data and interact with users through data insights ------------- Our members see more. Join us!
