List comprehension is powerful and must know concept in Python. Yet, this remains one of the most challenging topic for beginners. With this post, I intend help each one of you who is facing this trouble in python. Do you know List Comprehensions are 35% faster than FOR loop and 45% faster than map function? I discovered these and many other interesting facts in this post. If you are reading this, I'm sure either you want to learn it from scratch or become better at this concept. Both ways, this post will help you.

At your day job as a professional code Googler – I mean developer – you probably search for quick snippets multiple times a day to find the best way to perform a particular task. Almost always as developers we end up on Stack Overflow or Mozilla Developer Network, but now Microsoft's Bing has given us something even better: executable code directly in search results. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. Thanks to a collaboration with HackerRank, if you search for something like string concat C#, you'll get an interactive code editor with a result that can be run directly from that page to see how it works. It's a seriously fantastic feature that I hope Google adds soon – I'm not sure I'd switch search engine for this, but I'm incredibly jealous.

There's a new bot in town (Tokyo, specifically), and while it might not be as cute as Nao, as creepy as Spot and BigDog or as anthropomorphic as Atlas, it might be more practical than all of them. It walks on two legs, but not like a man, or even a bear. This one, designed by Alphabet-owned Schaft Inc., has its own uniquely robotic form of locomotion. A video then played showing robots like the one on stage, but different -- but all with a few things in common. Most important has to be the walking system.

When Dennis R. Mortensen hired his founding team members at x.ai, he pitched them by illustrating his vision of a world where everyone has a personal assistant to schedule their meetings. Recognizing the complexity of the challenge, he concluded by saying: "We may die trying." "It's a great setting to hire qualified people," Dennis says, recounting the late days of 2013. "We're working on something that is clearly very hard, to the extent that we might not make it, but it's not impossible." That's the sweet spot, he says.

Over the last year, in my spare time, I've built several small machine learning apps. For example, one that predicts the San Francisco fog at a neighborhood by neighborhood level. I have ideas for other things that I want to build, but at a much larger scale, for example large recommendation systems off Twitter's API. I've tried looking for tutorials or courses on how to build scalable machine learning apps, but I feel like I'm drowning in a lot of stuff I don't understand -- distributed architecture, MapReduce, Spark to name a few. Suggestions for the best way for a beginner to scale to get started?

On March 23, in an effort to appeal to a prime social media demographic, 18-24 year-old women, Microsoft launched a teen-girl-inspired chatbot named Tay. Less than a day later, the bot was swiftly removed from the site after tweeting things like "i fucking hate feminists"--and that's one of the tamer messages. In 2015, GE inaugurated a new, Multi-Modal manufacturing facility in Chakan, India. If the company's ambitions for the space are realized, it could drive a massive change in global manufacturing. But while the quick denigration of Tay's conversations may have been unexpected for Microsoft, most AI experts agree that it was inevitable.

The risk of cyberattacks is one of the most dangerous threats facing businesses today. And while new versions of attacks are constantly being born, teams of analysts are rushing to keep up with the latest risks. While many detection systems rely primarily on machine learning for catching attackers, a new AI system at PatternEx depends on human analysts as a vital part of their system of supervised machine learning. In 2015, GE inaugurated a new, Multi-Modal manufacturing facility in Chakan, India. If the company's ambitions for the space are realized, it could drive a massive change in global manufacturing.

There's a point on the Uncanny Valley when a humanoid robot turns from something "friendly" into something terrifying. An example of a robot that would naturally register as non-threatening would be Star Wars' C-3PO. We can still differentiate between computer and human at that level. It's familiar to us, but we know for a fact that it's non-human. Even though we see these robots in such a way, is it possible that we could associate them with a deeper emotional response?

You don't need a STEM background to make it in Silicon Valley. In fact, one of the most desirable skill sets these days in the tech capital of America has seemingly little to do with technology. So for all you struggling artists waxing poetic (literally), starve no more -- instead, you may want to consider making not a career change, but a change in scenery. As virtual assistants like Siri, Alexa, and Cortana grow in popularity, so too must their communication skills. And those skills have to come from humans who are particularly gifted in the realm of language.

At the Lawrence Livermore National Laboratory, scientists have begun testing IBM's TrueNorth computer chip--a brain-inspired mega chip IBM deems "the largest neurosynaptic chip" to date. IBM's TrueNorth is the first of its kind. A collaboration between IBM and Cornell University via the DARPA SyNAPSE Program, which was granted 100 million in public funding, the idea for the chip was conceived in 2004. In 2015, GE inaugurated a new, Multi-Modal manufacturing facility in Chakan, India. If the company's ambitions for the space are realized, it could drive a massive change in global manufacturing.