We are excited to announce that an AWS Deep Learning AMI for Ubuntu is now available in the AWS Marketplace in addition to the Amazon Linux version. The AWS Deep Learning AMI, now available on AWS Marketplace, lets you run deep learning in the Cloud, at any scale. Launch instances of pre-installed, open source deep learning frameworks, including Apache MXNet, to train sophisticated, custom AI models, experiment with new algorithms, and learn new deep learning skills and techniques. The AWS Deep Learning AMI lets you create managed, auto-scaling clusters of GPUs for large-scale training, or run inference on trained models using the latest versions of MXNet, TensorFlow, Caffe, Theano, Torch, and Keras. With the addition of an Ubuntu version, you have the choice to run on the operating system of your choice.

Employees stand outside the new Amazon Go grocery store in Seattle, Washington, U.S., on Tuesday, Dec. 6, 2016. Inc. unveiled technology that will let shoppers grab groceries without having to scan and pay for them -- in one stroke eliminating the checkout line. Are no-checkout stores like Amazon Go going to become common-place by 2025? Why or why not? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world. There is little doubt, many if not all of the concepts from the Amazon Go store will be adopted by A-level retailers over the next 5 years.

We want to hear how you would harness machine learning to have a truly positive effect on society. The ability to recognise patterns has been fundamental in the progression of modern civilisation: from sailors using the night sky to navigate the oceans, to scientists observing natural phenomena to construct theories of the world. With the advent of powerful computers and large datasets, these days machine learning (ML) is allowing computers to recognise patterns and learn from data like never before. You can already see this in the world around you: online retailers suggest products you might be interested in, your phone can translate spoken words to text on the screen and cars are learning to drive themselves. This year we've expanded the competition and encourage students aged 16 to apply.

Sudipta Mukherjee was born in Kolkata and migrated to Bangalore. He is an electronics engineer by education and a computer engineer/scientist by profession and passion. He graduated in 2004 with a degree in electronics and communication engineering. He has a keen interest in data structure, algorithms, text processing, natural language processing tools development, programming languages, and machine learning at large. His first book on Data Structure using C has been received quite well.

Bostjan Kaluza, PhD, is a researcher in artificial intelligence and machine learning. Bostjan is the chief data scientist at Evolven, a leading IT operations analytics company, focusing on configuration and change management. He works with machine learning, predictive analytics, pattern mining, and anomaly detection to turn data into understandable relevant information and actionable insight. Prior to Evolven, Bostjan served as a senior researcher in the department of intelligent systems at the Jozef Stefan Institute, a leading Slovenian scientific research institution, and led research projects involving pattern and anomaly detection, ubiquitous computing, and multi-agent systems. Bostjan was also a visiting researcher at the University of Southern California, where he studied suspicious and anomalous agent behavior in the context of security applications.

I thought this was a very well-written book on Deep Learning (DL). Java is (in my opinion) not the best language for teaching algorithms, but the example code is very readable. Like many DL books, the book focuses a lot on basic concepts and the math derivations behind them, so in that sense it is relatively undifferentiated from these books - however, it is is the only one that does so in Java. This is the only book I have read that has extensive coverage of pre-training (Deep Belief Networks, Restricted Boltzmann Machines, Denoising Autoencoders (DA), and Stacked DAs). Other "standard" networks such as Multilayer Perceptrons, Convolutional Neural Networks and Recurrent Neural Networks are also covered, about as well as other books I have read.

Jeff Heaton is a data scientist, PhD student and indy publisher. Specializing in Java, C#, C/C, Python and R, he is an active technology blogger, open source contributor, and author of more than ten books. His areas of expertise include predictive modeling, data mining, big data, business intelligence, and artificial intelligence. Jeff holds a Master's Degree in Information Management from Washington University. He is also a senior member of the IEEE, a Sun-Certified Java Programmer, the lead developer for the Encog Machine Learning Framework open source project, and a fellow of the Life Management Institute (FLMI).

Mobile has become an integral part of the shopping experience. As consumers spend more time with their mobile devices than with desktop and notebook computers combined, they're looking to their smartphones and tablets to complete more complex transactions. Yet, there is still room to grow for the retail industry's mobile experiences. While nearly one-third of retailer web traffic is from mobile devices, only 11 percent of sales come from mobile, according to Forrester's U.S. Mobile Phone and Tablet Commerce Forecast, 2015 - 2020. Mobile gives retailers opportunities to entice new customers, and retain returning customers, by allowing them to shop on their own terms.

Artificial intelligence and machine learning will create computers so sophisticated and godlike that humans will need to implant "neural laces" in their brains to keep up, Tesla Motors and SpaceX CEO Elon Musk told a crowd of tech leaders this week. While Musk's description of an injectable human-computer link may sound like science fiction, top tech executives repeatedly said that artificial intelligence (AI) was on the verge of changing everyday life, during discussion at a conference by online publication Recode this week. It is no secret that tech companies are diving into AI analytics research, an industry that will grow to $70 billion by 2020 from just $8.2 billion in 2013, according to a Bank of America report citing IDC research. AI, which combs through large troves of raw data to predict outcomes and recognize patterns, is already used in web search systems, marketing recommendation functions and security and financial trading programs. The technology will spread to driverless cars and service robots in the future, the Bank of America report said.

Most people have an Amazon Echo in their kitchen or living room - but the CEO of Amazon keeps one in his bathroom. In a recent interview with Billboard, Jeff Bezos revealed there is a smart speaker in every room of his house, including his water closet. The tech tycoon moved a device into the room after being frustrated when he could not ask Alexa about the weather while on the toilet. Most people keep an Amazon Echo in their kitchen or living room, but the CEO of Amazon has one in his bathroom. Amazon Echo is a voice-controlled smart speaker that works alongside a smartphone app.