This book is a nice introduction to using the Apache Spark framework. It assumes no prior knowledge of either Hadoop, Spark or machine learning itself (although the latter is covered at quite a rapid pace in places so some background would likely be helpful!). The code examples are presented in Python and (mainly) Scala, with examples that are reasonably well-described. The overall tone of the book is clear and the chapters progress in a logical order, with a fairly rapid journey through the main machine learning techniques from a Spark perspective. Later chapters were particularly interesting, covering text mining and more complex methods (e.g. Some of the example data sets feel a little'tired' (movie ratings data yet again - or perhaps I've just read too many machine learning books), but otherwise this is a good book and comes recommended.

The book provides a super fast, short introduction to Spark in the first chapter and then jump straight into MLlib, Spark Streaming Spark SQL, GraphX, etc. in subsequent chapters. A huge positive for this book is that it not only talks about Spark itself, but also covers using Spark with other big data technologies like Hadoop, Kafka, Titan, Neo4j, HBase, Cassandra, H2O, etc. True to the name, sure the book covers more than simple introductory Spark topics, but it concentrates on breath than depth. There is decent coverage and enough code examples for each topic, but what it lacks is depth. There is no "best practices" or "performance" or "watch out for" type discussions or any type of advanced code. The MLlib chapter covers Naive Bayes, K-Means and Artificial Neural Networks (ANN).

A nice balance of breadth and depth of you are already familiar with data science. If you are a data scientist this will give a nice review of topics that helps you pin point what you need to brush up on or quick primers to get you pointed in the right direction to study things you havent used much. I would strongly caution against using this book to learn a concept a new. Statistical concepts are given less weight and some are described with suboptimal accuracy. The programming/data engineering stuff is good and concise but maybe too brief for less CS oriented data scientists.

The authors have done an excellent job tying together state of the art academic concepts with state of the practice business needs, showing clearly how these two (much hyped) concepts can be used to provide value to our organizations. A must read for anyone confused about how to apply these concepts ...

Book has clear details of what to look at from spark application and configuration point of view to fine tune spark application execution in production environment. In this latest technology world, this books adds a lot of value to resources working in various shops gearing up their applications towards spark framework.

Pure-play online grocery retailer Ocado has announced the deployment of its machine learning-enhanced contact centre, which employs an advanced artificial intelligence software model to categorise customer emails. This novel approach ensures customers are still getting that familiar human touch while also benefiting from the quick response provided by technology automation. From the contact centre point of view, the customer service representatives don't have to spend hours categorising thousands of emails manually; instead, the artifical intelligence (AI) model parses the email and provides a useful summary and a priority tag. The customer service representative can then focus on solving the customers' problems in a timely manner. "We strive to deliver the best shopping experience for all our 500,000 active customers. However, working in an omni channel contact centre can be challenging, with the team receiving thousands of contacts each day via telephone, email, webchat, social media and SMS. The new software developed by the Ocado Technology data science team will help the contact centre filter inbound customer contacts faster, enabling a quicker response to our customers which in turn will increase customer satisfaction levels," said Debbie Wilson, Ocado's contact centre operations manager.

Students can now make their dream of making a robot friend come true. As a collaborative effort of SoftBank Robotics America and the on-campus clothing store the Ave at USC, a humanoid robot named Pepper will be visiting USC and staying on the third floor of the bookstore from Oct. 18 to Oct. 20. Pepper will be greeting the customers, informing them about the Ave and helping them customize shoes.

"It is a truth universally acknowledged that Jane Austen has been filling women with unrealistic expectation of men since 1813. Zoe Bunsen was one such woman. Twenty-eight and single, she'd never encountered a man as compelling as Mr. Darcy…" BUILDING MR. DARCY by Ashlinn Craven had me smiling from the onset. As a Jane Austen fan, I loved the idea of creating an AI (think Siri) who is the 2-D equivalent of a modern Mr. Darcy (well, mostly 2-D).

Imagine wanting a cup of coffee and suddenly finding it before you, freshly prepared to your exacting standards. In the not-so-distant future, this will be reality for Muggles, too. In fact, thanks to a surge in consumer data, brands and marketers can already make better inferences about consumer wants and needs, but as AI and machine learning are more deftly integrated, insights will only get better, as will the ability to anticipate consumer needs – and to even make decisions on behalf of consumers without any input from them whatsoever. Like, say, ordering a cup of coffee. As it stands, digital enables brands to customize offers for specific users rather than provide generic solutions.

Google has made minimal forays into real-world retail shops thus far. There's a good reason for that: the company has long been more focused on software than hardware. That's slowly changing over time, but Google went all-in on its own hardware brand when it announced the new Pixel smartphones, Google Home, Daydream VR headset and Google WiFi router earlier this month. For most consumers, buying hardware sight-unseen is still a tough proposition, so Google is finally making it easier for consumers to check out all its new gadgets -- in New York City, at least. The company's pop-up retail location opened its doors this morning, and while it wasn't exactly an iPhone-level stampede, there were a couple dozen people waiting to get in when it opened.