background preloader

Machine Learning et Big Data : définition et exlications de la combinaison

Machine Learning et Big Data : définition et exlications de la combinaison

Related:  cvs2Projet Collaboratif - IA et formationIADeep fake / IA dans médias / Face Swappingcps_pearltrees

Distractions tempt us at every turn, from an ever-growing library of Netflix titles to video games (Animal Crossing is my current vice) to all of the other far more tantalizing things we could be doing instead of doing what actually needs to be done. Is there any hope to focus on the things that matter in a world that wants us to do everything all the time? Spoiler: the answer is yes. Nir Eyal, avid Pocket user and author of Hooked: How to Build Habit-Forming Products and Indistractable: How to Control Your Attention and Choose Your Life, sat down with us to share his insights on how to beat distraction and stop feeling guilty about watching YouTube videos or playing Animal Crossing on your downtime. How did you start using Pocket and what keeps you coming back? Pocket features prominently in my book Indistractible.

Deep learning, education and the final stage of automation: Educational Philosophy and Theory: Vol 50, No 6-7 Credit Neuroscape Lab every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. – J. McCarthy, M. Imagine someone creating a deepfake video of you simply by stealing your Facebook profile pic. The bad guys don't have their hands on that tech yet, but Samsung has figured out how to make it happen. Software for creating deepfakes -- fabricated clips that make people appear to do or say things they never did -- usually requires big data sets of images in order to create a realistic forgery. Now Samsung has developed a new artificial intelligence system that can generate a fake clip by feeding it as little as one photo. The technology, of course, can be used for fun, like bringing a classic portrait to life. The Mona Lisa, which exists solely as a single still image, is animated in three different clips to demonstrate the new technology.

How to Create a Customer Journey Map – UX Mastery Despite best intentions and mountains of data, many organizations continue to offer lackluster experiences for their customers. Many organizations function with an internal focus, and that becomes apparent when customers interact with their various products, services and employees. Every interaction a customer has with an organization has an effect on satisfaction, loyalty, and the bottom line. Plotting out a customer’s emotional landscape by way of a Customer Journey Map, or Experience Map, along their path sheds ­­­­light on key opportunities for deepening those relationships. A Customer Journey map is a visual or graphic interpretation of the overall story from an individual’s perspective of their relationship with an organization, service, product or brand, over time and across channels.

The Oculus PC app v18 update improves the accuracy of positional tracking prediction for Oculus Link. Improved translation accuracy on predicted-poses. This improves the visual stability of up-close content under fast head motion. Learning Experience Platform (LXP): The Definitive Guide [2019] Discover: Organizations have been using Learning Management Systems (LMSs) for a long time now. But as training requirements started changing, company executives, learning professionals and learners realized that there was something missing. This post is a high-level introduction to Octalysis, the Gamification Framework I created after more than 17 years of Gamification research and and Behavioral Design study. Within a year of publication, Octalysis was organically translated into 16 languages and became required literature in Gamification instruction worldwide. What is Gamification? Gamification is design that places the most emphasis on human motivation in the process. In essence, it is Human-Focused Design (as opposed to “function-focused design”).

Inside a Student’s Hunt for His Own Learning Data Institutions have access to more student data than ever before—but it's hard to really grasp what that means, since many of the digital tools that colleges use are from third parties or companies that keep their algorithms private. That makes it hard for students, professors or even journalists to get a glimpse inside. That didn’t stop Bryan Short, who was a student at the University of British Columbia in 2016 when he got curious to know what information the learning management system at his university had collected on him and how it was being used. And what he found—that is, once he got a hold of it—left him feeling pretty uneasy. These days Short is a program director at the BC Freedom of Information and Privacy Association. EdSurge caught up with him recently to hear the story about his hunt for his own data and what he thinks colleges could do to make that technology a bit more transparent.

Sandeep Gupta, a technology manager in California, sees the economic storm caused by the coronavirus as a time “to try to future-proof your working life.” So he is taking an online course in artificial intelligence. Dr. Robert Davidson, an emergency-room physician in Michigan, says the pandemic has cast “a glaring light on the shortcomings of our public health infrastructure.” So he is pursuing an online master’s degree in public health. An intuitive, high-level framework to understand the technical trends in Artificial Intelligence I was recently reading this article titled “AI Is About to Learn More Like Humans — with a Little Uncertainty” which I found very interesting because it is tackling a core debate in AI today. However, I thought it was not straightforward to fully understand it so I wanted to take a step back and try to explain what is at stake behind this article, connecting ideas to provide more background and more concrete examples. I am suggesting a framework that I think relevant although it certainly contains necessary simplifications.

What is Learning Analytics? - Society for Learning Analytics Research (SoLAR) LEARNING ANALYTICS is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs, as defined back in 2011 for the first LAK, this general definition still holds true even as the field has grown. Learning analytics is both an academic field and commercial marketplace which have taken rapid shape over the last decade. As a research and teaching field, Learning Analytics sits at the convergence of Learning (e.g. educational research, learning and assessment sciences, educational technology), Analytics (e.g. statistics, visualization, computer/data sciences, artificial intelligence), and Human-Centered Design (e.g. usability, participatory design, sociotechnical systems thinking).

How AI is transforming e-learning - examples of artificial intelligence in education – Software House That Helps You Innovate - Neoteric Massive Open Online Courses (MOOCs) made education accessible to anyone with internet access. As reported by Class Central, in 2018, there were 101 million learners enrolled in MOOCs, with the top platforms being: Coursera with 37 million learners, edX with 18 million, XuetangX with 14 million, Udacity with 10 million, and FutureLearn with 8.7 million. More than 900 universities in the world offer MOOCs courses, including higher education degrees. Real World Examples Of Today And A Peek Into The Future While the debate regarding how much screen time is appropriate for children rages on among educators, psychologists, and parents, it’s another emerging technology in the form of artificial intelligence and machine learning that is beginning to alter education tools and institutions and changing what the future might look like in education. It is expected that artificial intelligence in U.S. education will grow by 47.5% from 2017-2021 according to the Artificial Intelligence Market in the US Education Sector report. Even though most experts believe the critical presence of teachers is irreplaceable, there will be many changes to a teacher’s job and to educational best practices.

Examples of how AI is Transforming Learning and Development August 16, 2019 - Dom Barnard - 9 min read Many of the products and services we use every day are already leveraging Artificial Intelligence (AI) to improve the user’s experience. Amazon uses machine learning to recommend products to you based on information it has collected. Google Home, Apple’s Siri and Microsoft’s Alexa use AI heavily in speech-to-text conversion and optimization. Your email service probably uses AI to fight spam emails and prevent them from landing in your inbox. The use of AI is all around us and can bring great benefits to the Learning and Development (L&D) sector and ultimately, the workforce also.