Guest blog by Sebastian Raschka, originally posted here. If we tackle a supervised learning problem, my advice is to start with the simplest hypothesis space first. I.e., try a linear model such as logistic regression. If this doesn't work "well" (i.e., it doesn't meet our expectation or performance criterion that we defined earlier), I would move on to the next experiment. I would say that random forests are probably THE "worry-free" approach - if such a thing exists in ML: There are no real hyperparameters to tune (maybe except for the number of trees; typically, the more trees we have the better).

Summary: What do you need to do to get an entry level job in data science? This article is written for anyone who is considering becoming a data scientist. That includes young people just starting their bachelor's degrees and folks in the first two or three years of their careers who want to make the switch. It's not for folks who know they are going to pursue one of the new Master's in Data Science or Ph.D. candidates. It's for folks looking for entry level jobs that are specifically on the data science career ladder.

Cornell University wants to help whales avoid getting hit by ships, so it is working on an algorithm that uses audio recordings to alert ships to the whales' whereabouts. Dassault Systèmes is creating a 3D model of a human heart that will allow surgeons to test the performance of pacemakers before opening up patients. Sure, machine learning has already had a significant impact on the worlds of science and culture, and in life, but it will be years before CIOs need to start worrying about enterprise machine learning applications ... right? "If CIOs invested in machine learning three years ago, they would have wasted their money," Olley says. "But if they wait another three years, they will never catch up."

Swedbank has gone live with Nuance Nina, a virtual assistant that delivers a human-like, conversational customer service. The system, provided by US-based Nuance Communications, sits on the Swedbank website and the bank's customers can type their questions to the virtual assistant. Swedbank customer service agents are also using the system to source information for customers. Martin Kedbäck, channel management at Swedbank, says: "We like to be where our customers are, and that includes providing support online and in our other digital channels." Nuance says Nina has helped Swedbank improve customer experience, including a 78% "first-contact resolution within the first three months". Customer adoption has seen an average of 30,000 conversations per month within the same period; and it is currently answering eight out of every ten customer questions.

Google wants to put its artificial intelligence technology to use in top hospitals. Earlier this week, the search giant announced it would work with the U.K.'s National Health Service, or NHS, to alert staff to patients at risk of serious complications due to kidney failure. Details about the technology are fairly thin on the ground at this stage. But it is known that Google DeepMind recently acquired an app called Hark, which is a task management app that aims to replace paper-based systems and pagers. Hark was developed over four years by a team at Imperial College London, which is one of the U.K.'s top medical schools.

Artificial Intelligence has been the topic de jour lately with every corner of intellectual thought sounding in on the perils, and the potential rewards, of synthesizing a machine intelligence that could successfully perform any intellectual task that a human can. Elon Musk, Bill Gates and even Stephen Hawking have all suggested that an AI with this sort of general intelligence (also known as Strong AI or Full AI) could bring about an apocalypse that sees an end to human civilization, or even an end to the human race. There's no doubt that Strong AI is the subject of intense research by DARPA, MIT, Berkeley, IBM, Google and many others. But it's hard not to notice that despite all the anxiety, Strong AI today lives only in the imagination of science fiction writers and in the hopes and dreams of research scientist. At the prestigious "Future of AI" conference in San Juan this January, the estimates for when an AI might emerge vacillated wildly from 5 years to a hundred years in our future--its variables are that unknown.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Drive.ai is the 13th company to be granted a license to test autonomous vehicles on public roads in California. This is exciting news, especially because we had no idea that Drive.ai even existed until just last week. The company has been in stealth mode for the past year, working on applying deep learning techniques to self-driving cars. We spoke with two of Drive.ai's Its core team is made up of experts with a wealth of experience developing deep learning systems in all kinds of different domains, including natural language processing, computer vision, and (most recently) autonomous driving. "This team helped pioneer how to scale deep learning, which is one of the reasons why deep learning has been successful as of late," says Tandon, the company's CEO.

A Chinese automaker announced the successful road trip of its self-driving cars. Two of the vehicles have completed the travel across China, which lasted for six days and covered more than 1,200 miles. Chinese automaker and Ford's partner Chongqing Changan Automobile Co. announced the successful road trip of its self-driving car. The vehicle traveled from Chongqing in Southwest China to Beijing, which is in the northeast. The journey covered more than 1,200 miles (almost 2,000 kilometers) and lasted for six days - that's an average of 200 miles (321.8 kilometers) a day.

When British mathematician Sir Andrew J. Wiles was awarded the Abel Prize Laureate in math on 15 March for cracking a centuries-old hypothesis, a friend asked me, "Why did he get the prize, and will this solve any real-world problem?" Quoting from the statement that the Norwegian Academy of Science and Letters gave to the press, I told him that 63-year-old Wiles had been given the annual award "for his stunning proof of (French mathematician Pierre de) Fermat's last theorem by way of the modularity conjecture for semi-stable elliptic curves, opening a new era in number theory". So let me try to simplify it a bit. Number theory--also sometimes referred to as the "queen of mathematics" or "higher arithmetic"--is a branch of pure math, devoted primarily to the study of the properties of whole numbers. Fermat--a prominent mathematician of the 17th century--contributed significantly to number theory, probability theory, analytic geometry and the early development of infinitesimal calculus. Fermat's last theorem states that no three positive integers a, b, and c satisfy the equation an bn cn for any integer value of n that is greater than two.