Building an analysis ecosystem for a smarter approach to intelligence

Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people’s behaviors, and how to unobtrusively provide better services.

This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks.

This book provides an overview of current issues and challenges in the fashion industry and an update on data-driven artificial intelligence (AI) techniques and their potential implementation in response to those challenges. Each chapter starts off with an example of a data-driven AI technique on a particular sector of the fashion industry (design, manufacturing, supply or retailing), before moving on to illustrate its implementation in a real-world application

This book series publishes monographs and edited volumes from leading scholarsand established practitioners in the fashion business. Specific focus areas such asluxury fashion branding, fashion operations management, and fashionfinance andeconomics, are covered in volumes published in the series.

Rather than spend $30-$50 USD on a dense long textbook, you may want to read this book first. As a clear and concise alternative to a textbook, this short book offers a practical and high-level introduction to the practical components and statistical concepts found in machine learning.

The book Big data @ work: Dispelling the Myths, Uncovering the Opportunities, Go ahead, be skeptical about big data. Analytics expert and bestselling author Tom Davenport was--at first. When the term ""big data"" entered the scene, Davenport (Competing on Analytics, Analytics at Work) thought it was just technology hype.

With a focus on leveraging big data, the book provides expert guidance on developing an analytical ecosystem to effectively manage, use the internal and external information to deliver business results.

Sales and service are being radically redefined by the biggest communications revolution in human history. Today buyers are in charge! There is no more 'selling'—there is only buying. When potential customers have near perfect information on the web, it means salespeople must transform from authority to consultant, product narratives must tell a story, and businesses must be agile enough to respond before opportunity is lost.

Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters.