As readers of my blog will know, I want to learn more about machine learning. I've managed to run some samples, and I've built my own first little samples. It feels like the next step is to understand more about the different algorithms, for example when to pick which one and how to tune the parameters to achieve the best results. To learn more, I've started to watch the first hours of the awesome courses below. The courses are a great introduction to machine learning and very different from most other videos I found which often seem to assume you are already a data scientist.

When a very young child looks at a picture, she can identify simple elements: "cat," "book," "chair." Now, computers are getting smart enough to do that too. In a thrilling talk, computer vision expert Fei-Fei Li describes the state of the art -- including the database of 15 million photos her team built to "teach" a computer to understand pictures -- and the key insights yet to come. TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and much more.

How important are skills in computational thinking for computing app constructors and for computing users in general? If we can teach our children early on to smile, talk, write, read, and count through frequent and repetitive use of patterns in well-chosen examples, is it also possible for us, assuming we have the skills, to teach our children to construct computing applications? Do we need to first teach them anything about computational thinking before we look to teach how to construct computing apps? If not, how important will computational skills be for us all, as Jeannette Wing suggests in her blog@cacm "Computational Thinking, 10 Years Later" (Mar. Many competent and successful computing app constructors and users never hear a word about computational thinking but still manage to acquire sufficient construction and user skills through frequent and repetitive use of patterns in well-chosen examples.

That is what I said when I was asked whether we would ever see computer science taught in K–12. It was 2009, and I was addressing a gathering of attendees to a workshop on computational thinking (http://bit.ly/1NjmcRJ) It has been 10 years since I published my three-page "Computational Thinking" Viewpoint (http://bit.ly/1W73ekv) in the March 2006 issue of Communications. To celebrate its anniversary, let us consider how far we've come. Since the dotcom bust, there had been a steep and steady decline in undergraduate enrollments in computer science, with no end in sight.

The ability to make continual, accurate decisions based on evolving data is key in many of today's data-driven intelligent systems. This tutorial-style talk presents an introduction to the modern study of sequential learning and decision making under uncertainty. The broad objective is to cover modeling frameworks for online prediction and learning, explore algorithms for decision making, and gain an understanding of their performance. Specifically, we will look at multi-armed bandits- models of decision making that capture the explore-vs-exploit tradeoff in learning, regret minimization, non-stochastic or adversarial online learning, and online convex optimization. Time permitting, we will discuss new directions and frontiers in the area of sequential decision making.

The AI analyzes student answers, and groups them based on similarity.

Virtual patients are becoming a useful tool for medical students and a resource for medical schools. The obvious reality that students can make mistakes with no risk to the "patient" is part of the attraction to this technology. "Virtual patients allow students to learn without putting real patients at risk," said Norm Berman, MD, professor of pediatrics at the Geisel School of Medicine at Dartmouth and the lead author of a perspective piece recently published by the journal Academic Medicine. "No actual patients are harmed in the process of learning from virtual patients." The authors outlined the role of virtual patients in relation to the challenges and opportunities within medical education.

NIIT, a global leader in skills and talent development, today launched a course in Web App Development with MEAN Stack under the DigiNxt Series. The company has recently ventured into Digital Transformation to offer pioneering programs to young aspirants wishing to enter the digital services industry, as well as to IT professionals wishing to reskill themselves for the new digital world. The cutting-edge program will use the student-centred pedagogy of project-based learning to help them carve a successful career in the emerging digital era. Some of the famous web applications like LinkedIn, Netflix, Uber, Paypal, etc. have been built using MEAN Stack. AngularJS, Node.js (MEAN) represents a group of open source technologies which are known to synergize well together, thereby empowering students to launch their own web and mobile apps.

A school in London is set to become the first in Britain to welcome a robot teacher when it opens in September. The humanoid robot, known as Pepper, will be used in classrooms at the London Design and Engineering University Technical College, to help teach pupils about cutting-edge robotics. It will be the first instance of an educational robot being used in a UK classroom. Claims made by an expert in artificial intelligence predict that in less than five years, office jobs will disappear completely to the point where machines will replace humans. The idea that robots will one day be able to do all low-skilled jobs is not new, but Andrew Anderson from UK artificial intelligence company, Celaton, said the pace of advance is much faster than originally thought.

The Amazon Echo is an unlikely hit. After all, the world's largest online retailer hasn't always won its bets on hardware. And a gadget that relies solely on voice? Yet Amazon has by one estimate sold some 3 million of the squat cylinders since the Echo launched in November, 2014. The company doesn't share sales data, but it did say Alexa, the voice-activated software that powers Echo, is active in millions of places, including smartphone apps and other Amazon gadgets.