Earlier, we came up with a list of some of the best Machine Learning books you should consider going through. In this article, we have come up with yet another list of the recommended books for Data Science. Written by Hopcroft and Kannan, this book is a great blend of lectures in the modern theoretical course in data science. This tutorial aims to get you familiar with the main ideas of Unsupervised Feature Learning and Deep Learning. The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages.

We surveyed 835 executives in companies (average revenue of $20 billion and median of $2.8 billion) from 13 industries across North America, Europe, Asia-Pacific, and Latin America. North America Firms in the region spent most on AI in 2015: $80 million on average. Europe European firms are catching up: they plan to invest $80 million on average (26% more than North America) in 2016. Latin America Companies here achieved the biggest revenue gains and the highest cost reduction through AI, while investing less than other regions. Asia-Pacific Companies invested $55 million, on average, in AI in 2015.

Right now it's easiest to think about an artificial intelligence algorithm as a specific tool, like a hammer. A hammer is really good at hitting things, but when you need a saw to cut something in half, it's back to the toolbox. Train an facial recognition algorithm, but don't ask it to recognize cows. Alphabet's AI research arm, DeepMind, is trying to change that idea with a new algorithm that can learn more than one skill. Having algorithms that can learn multiple skills could make it far easier to add new languages to translators, remove bias from image recognition systems, or even have algorithms use existing knowledge to solve new complex problems.

Computer programs that learn to perform tasks also typically forget them very quickly,

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Imagine owning a smartphone or TV that could roll up to fit in your pocket. That could soon be reality thanks a new flexible sensor that can detect subtle differences in touch, including swiping and tapping. Researchers said their stretchable sensor could be used to build folding TV screens and tablets - and may even be used to make skin for robots. The team from the University of British Columbia in Vancouver used a highly conductive gel sandwiched between layers of silicone to make their bendable sensor. To create the sensor, a gel is poured out and combined with silicon-based materials that are stretchy and transparent.

Last week, we (and most of the rest of the internet) covered some research from MIT that uses a brain interface to help robots correct themselves when they're about to make a mistake. This is very cool, very futuristic stuff, but it only works if you wear a very, very silly hat that can classify your brain waves in 10 milliseconds flat. At Brown University, researchers in Stefanie Tellex's lab are working on a more social approach to helping robots more accurately interact with humans. By enabling a robot to model its own confusion in an interactive object-fetching task, the robot can ask relevant clarifying questions when necessary to help understand exactly what humans want. Whether you ask a human or a robot to fetch you an object, it's a simple task to perform if the object is unique in some way, and a more complicated task to perform if it involves several similar objects.

An automated test vehicle equipped with Bosch technology. On the heels of Intel's $15.3 billion plan to buy computer vision powerhouse Mobileye to lock in a big piece of the automated car tech market, Nvidia and Bosch are teaming up to make an AI-enabled computer that can be mass-produced to serve as the brains for driverless vehicles. The Silicon Valley maker of graphics processors and its new German partner, which ranks among the world's largest auto parts makers, will develop a computer that utilizes Nvidia's deep learning software and Drive PX processor, Bosch CEO Volkmar Denner announced at Bosch's ConnectedWorld conference in Berlin. Financial details for the project weren't included in their statement, and Nvidia and Bosch both declined to elaborate. "Bosch will build automotive-grade systems for the mass production of autonomous cars," Nvidia CEO and founder Jen-Hsun Huang said in the statement.

Technically it ain't brain surgery, but let's just say you wouldn't want to do a cochlear implant while sleepy or distracted. So it's a good thing this surgery robot can't be either of those things. The bit passes just half a millimeter from the facial nerve, and another half a millimeter from the taste nerve, before entering the spiraling cochlea of the inner ear. The first robot-assisted cochlear implant in a clinical trial, which researchers describe today in the journal Science Robotics, doesn't just enhance a surgeon's dexterity like the by-now-common da Vinci robot might. "We are interested in doing something with the robot that a surgeon is not able to do," says study co-author Stefan Weber of the ARTORG Center for Biomedical Engineering Research.

Xero has introduced what it says is the first personalised machine learning capability for a small business cloud accounting system. Its main role is to automatically allocate the correct account code to invoices. Xero says it uses detailed statistical analysis to learn from and assist the individual business and their partner based on their own specific circumstances. "The automation will mean small businesses no longer need to worry about where their invoice is filed - an invoice for time spent on site should be recorded against'Sales – Labour', not'Sales – Materials', for instance." According to Xero there are more than 10.1 million unique account codes in Xero created by small businesses, meaning items are often entered incorrectly, creating hours of work for the accountants who need to correct them.