Bots have officially taken over, and they're about to make our lives a whole lot easier. In April, Facebook introduced bots for Messenger, but the world's most popular social media platform is not the only company to open a "bot store" with consumer functions, and virtual assistants like Amazon's Alexa are steadily increasing in both popularity and functionality. With Kik, you can chat with Michelangelo and see the climate conditions through Yahoo! With Operator, shopping is as easy as sending a text, and Pana, the online travel agency, turns a simple chat conversation via text into real bookings. In fact, everyone from 1–800-Flowers and the NBA to Taco Bell is jumping on the chatbot bandwagon.

An Amazon warehouse is a flurry of activity. Towering hydraulic arms lift heavy boxes toward the rafters. And an army of stubby orange robots slide along the floor like giant, sentient hockey pucks, piled high with towers of consumer gratification ranging from bestsellers to kitchenware. Those are Kiva robots, once the marvel of warehouses everywhere. Amazon whipped out its wallet and threw down US 775 million to purchase these robot legions in 2012.

If Dr. Chan is actually a doctor in anything, I doubt if it has anything to do with actual trading. Lots of useless screenshots of forex data price charts with single Metatrader indicators on them. The book is not worth reading even if you were paid to read it,. None that I've met or worked with.

Amazon's (NASDAQ:AMZN) artificial intelligence Alexa can now place orders on Amazon, making it even easier for shoppers to use the service with more frequency. Alexa is the digital voice assistant inside the company's Echo Bluetooth speakers. It previously could only re-order items that had already been purchased, but now it can order anything that is available to Amazon Prime members, with some exceptions. Users simply ask Alexa for a product available with Prime, she makes a suggestion, reports the price and a simple "yes" buys it. There are millions of items now available for ordering through Alexa and quite a few that are not, including Amazon Fresh, Amazon Prime Pantry and Amazon Prime Now items.

Now you can talk into your friendly little home AI tower to order toilet paper. And tens of millions of other Amazon Prime qualified products, because no one does synergy quite like the good people at Amazon. The retail-super-mega-giant, which had previously enabled reordering through Alexa, is now adding search/shopping to its AI voice assistant. Users with Amazon Echo, Echo Dot, Tap or Fire TV can shop for new products by saying, say, "Alexa, order a Frisbee," at which point the program will suggest a relevant Prime product and price. Say "yes," and, well, you've probably ordered a product on Amazon at some point, so you know how the rest of this deal goes.

Over the years, a world full of supermarkets and shopping malls has desensitized our relationship with the environment and each other. We no longer know where our food or clothes come from, and the cashier will only make eye contact to take our payment. By contrast, when shopping online, it seems that almost every website knows all of our preferences in a personalized experience. FiveStars is a loyalty and shopping analytics platform for small brick-and-mortar retailers that aims to restore the balance. FiveStars has logged more than 35 million visits from 10 million consumers who have used the loyalty app through over 10,000 merchants.

If you have used (or attempted to use) Giraph you will know that it's not the easiest system to pick up and start getting your hands dirty. However, it is an extremely powerful tool that can be used to solve many interesting problems at scale. This book does a great job of taking you from the very beginning with simple, straightforward algorithms to more complex real-world applications and finally more advanced topics (e.g., data partitioning, out-of-core algorithms, running on the cloud, etc.). With this book you can start without knowing anything about Giraph or distributed graph processing systems in general (or even about graphs!) and learn how to solve many graph problems at scale. There are several things that I find so appealing about this book. The main things are: (1) the _numerous_ examples with step-by-step illustrations that help you understand what exactly is happening during an algorithm, (2) the fact that the example applications are motivated by real-world problems (e.g., recommendation systems, pagerank, etc.) whose solutions can then serve as a building block for your personal applications, and (3) the example code that will allow you to quickly get your hands dirty and start playing with the tool.

This is an excellent book both in depth and breadth of the topics covered. It gives descriptions, analyses, and insights about the most popular algorithms on various topics, and it covers many more areas than most books. The book is well integrated across the broad diversity of topics that are covered, and connections between methods and topics are pointed out throughout the book. I wouldn't agree with an earlier review that the descriptions are short or introductory. For most of the important topics, a lot of detail is provided in terms of algorithm description and pseudo-code.

An Amazon warehouse is a flurry of activity. Towering hydraulic arms lift heavy boxes toward the rafters. And an army of stubby orange robots slide along the floor like giant, sentient hockey pucks, piled high with towers of consumer gratification ranging from bestsellers to kitchenware. Those are Kiva robots, once the marvel of warehouses everywhere. Amazon whipped out its wallet and threw down 775 million to purchase these robot legions in 2012.

Scala is a programming language that makes it possible to write terse but efficient code. In today's fast paced world, learning languages like Scala pay great dividends when solving complex problems like building recommendation engines to optimize the customer experience. The big players like Google, Amazon, Linkedin and Facebook all employ recommendation engines to keep the customer coming back for more. The author of this book assumes no prior experience with Scala and starts from the beginning, explaining how to install Scala, the Scala Build Tool and Apache Spark. The author combines these with Apache Kafka and MongoDB to build a data processing pipeline able to glean upto the minute insights into customer data.