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Apache Spark deep learning cookbook : over 80 recipes that streamline deep learning in a distributed environment with apache spark / Ahmed Sherif, Amrith Ravindra
Birmingham, UK : Packt Publishing, 2018
462 pages. : illustrations ; 24 cm.
Ký hiệu phân loại (DDC): 006.31
With the help of the Apache Spark Deep Learning Cookbook, you'll work through specific recipes to generate outcomes for deep learning algorithms, without getting bogged down in theory. From setting up Apache Spark for deep learning to implementing types of neural net, this book tackles both common and not so common problems to perform deep learning on a distributed environment. In addition to this, you'll get access to deep learning code within Spark that can be reused to answer similar problems or tweaked to answer slightly different problems. You will also learn how to stream and cluster your data with Spark. Once you have got to grips with the basics, you'll explore how to implement and deploy deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in Spark, using popular libraries such as TensorFlow and Keras
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HBR guide to data analytics basics for managers.
Boston, Massachusetts : Harvard Business Review Press,2018
x, 231 p. ; 23 cm.
Ký hiệu phân loại (DDC): 658.4033
Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data, but leaving the analysis to others in your company just won't cut it. Now more than ever, managers must know how to tease insight from data--to understand where it comes from, make sense of the numbers, and use those findings to inform their toughest decisions. But how do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes a three-step process to get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Formulate hypotheses and test against them Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes--
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