It's all about trying to teach computers to make connections, similar to those humans make instinctively when growing up, in distinguishing objects. When it comes to video content, machine learning can help solve one of the growing issues in the industry. Barry Schwarz calls it'the paradox of choice' which he describes in his book and his excellent TED talk. Simply put, there has been an explosion of high quality video content production over the last decade. In 2014, Annalect reported that US consumers wanting to watch episodic TV had over 350 to choose from. Yet, consumers are less happy now than when they had fewer choices. It turns out that too many choices just make decisions harder. So, as an industry, we must come up with new ways of getting a better understanding of what each consumer wants to watch and create tools that will make discovery and recommendation more seamless and effective. In fact, machine learning could very well be the driver of a completely new set of content discovery and hyper-personalized services that will dramatically improve viewer satisfaction.

The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

Artificial intelligence is going to change everything in every industry. Not so fast, says Coursera president and co-founder Daphne Koller. Her education company markets itself as being ahead of technological disruption, but even it isn't so sure AI can do everything that a human college professor can do. "Instructors are valuable, first of all, in creating the content. That's really important," Koller said in an interview with Recode's Kara Swisher on the latest episode of Recode Decode.

When people discuss the workplace of the future, they frequently focus on the collaboration technologies and the layout of these new workspaces. We discuss the "intolerance" of millennials and how work tools must change to support the digital native. While the selection of tools is important, this dialogue lacks a discussion of the type of jobs employees will perform and how they'll be trained to do these jobs. We're entering the next generation of the industrial revolution and today's workforce is largely unprepared to fill the next wave of jobs. Many careers in the future will be based on software programing, machine learning and data analysis using tools that barely existed ten year ago.

What could be more convenient than upgrading skills online? There are plenty of courses / certifications available to kick-start your career in analytics. These courses are provided in online, offline or hybrid mode. The only difficulty students face is to decide the best out of these courses. With some newly introduced courses, it has become even more difficult to make a convincing decision. The fear of investing in unworthy courses continues to remain the biggest hurdle for students. Last year, I received thousand of emails after I published Top Certifications on SAS, R, Python, Machine Learning. Later, I came to know that my analysis helped many people in deciding the best course for themselves. The year 2016 is no different either. I am back with my thorough analysis and rankings of best certifications courses in India. I assure you these rankings are unbiased. Last month, we released our rankings on Top Business Analytics Programs in India 2015-16. If you too are planning for a degree in analytics, you may like to consider these institutes. In this article, I'll focus on ranking short duration and certification courses. I've considered the courses which are delivered in online or hybrid mode.

Learning needs to be less like memorization, and more like…Angry Birds. Half of school dropouts name boredom as the number one reason they left. The post is about why the future of education will be about flipping our current model on its head and about how key exponential technologies like AI, VR and gamification are going to drive a revolution in education. In the traditional education system, you start at an "A," and every time you get something wrong, your score gets lower and lower. You start with zero, and every time you come up with something right, your score gets higher and higher.

This rather long read article from Nautilus does a great job on showing the current landscape of a quite new type of medical research aimed at curing aging and eventually curing death. It feels like the technology is almost here. The big players are getting interested in the research as they get older. The hype is getting real. Augmented humans that combine technology and biology, including apps for the brain and hard drives wired straight into people's veins are just around the corner, according to a business software company.

Currently, more than 30 million people in the world have speech impairments and thus to communicate have to use sign language resulting in a language barrier between sign language and non-sign language users. This project explores the development of a sign language to speech translation glove by implementing a Support Vector Machine(SVM) on the Intel Edison to recognize various letters signed by sign language users. The data for the predicted signed gesture is then transmitted to an Android application where it is vocalized. The sign language glove has five flex sensors mounted on each finger to quantify how much a finger is bent. Flex sensors are sensors that change their resistance depending on the amount of bend on the sensor.

Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It's incredible, but it can also be overwhelming. That's why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments.

This unusual book describes the nature of statistics by displaying multiple examples of the way the field has evolved over the past sixty years, as it has adapted to the rapid increase in available computing power. The authors' perspective is summarized nicely when they say, 'very roughly speaking, algorithms are what statisticians do, while inference says why they do them'. The book explains this'why'; that is, it explains the purpose and progress of statistical research, through a close look at many major methods, methods the authors themselves have advanced and studied at great length. Both enjoyable and enlightening, Computer Age Statistical Inference is written especially for those who want to hear the big ideas, and see them instantiated through the essential mathematics that defines statistical analysis. It makes a great supplement to the traditional curricula for beginning graduate students.