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Until recently, many people thought big data was a passing fad. "Data science" was an enigmatic term. Today, big data is taken seriously, and data science is considered downright sexy. With this anthology of reports from award-winning journalist, Mike Barlow, you'll appreciate how data science is fundamentally altering our world, for better and for worse. Barlow paints a picture of the emerging data space in broad strokes. From new techniques and...

Jean-Georges showcases how to use JHU data to predict new Covid-19 cases using Apache Spark. He's the author of Spark in Action, Second Edition.

Leverage the capabilities of SAS to process and analyze Big Data About This Book Combine SAS with platforms such as Hadoop, SAP HANA, and Cloud Foundry-based platforms for effecient Big Data analytics Learn how to use the web browser-based SAS Studio and iPython Jupyter Notebook interfaces with SAS Practical, real-world examples on predictive modeling, forecasting, optimizing and reporting your Big Data analysis with SAS Who This Book Is For SAS professionals...

A presentation from the Strata Data 2017 London conference. "Miguel González-Fierro explains how to train a state-of-the-art deep neural network, ResNet, using Microsoft RSever and MXNet with the ImageNet dataset. (While most of the deep learning libraries are programmed in C++ and Python, only MXNet offers an API for R programmers.) Miguel then demonstrates how to operationalize this training for real-world business problems related to image classification."--Resource...

A collection of blog posts written for oreilly.com organized around six key themes: careers in data; tools and architecture for big data; intelligent real-time applications; cloud infrastructure; machine learning, models and training; deep learning and AI. Cf. Introduction.

"To tackle the challenges of Big Data, novel approaches and tools have emerged. Moreover, the technology required for big-data computing is developing at a satisfactory rate due to market forces and technological evolution. This book presents a mix of theory and industry cases that discuss the technical and practical issues related to Big Data in intelligent information management. It emphasizes the adoption and diffusion of Big Data tools and technologies...

Entity Information Life Cycle for Big Data walks you through the ins and outs of managing entity information so you can successfully achieve master data management (MDM) in the era of big data. This book explains big data's impact on MDM and the critical role of entity information management system (EIMS) in successful MDM. Expert authors Dr. John R. Talburt and Dr. Yinle Zhou provide a thorough background in the principles of managing the entity...

Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the problem at hand. In the process of reading through these problems, you will learn harness the power of new big data opportunities which various enterprises...