Artificial intelligence is advancing at a rocket's pace, and every year the field looks fundamentally different than the year before. It's often difficult to keep up with all the news and exciting results. The best way I've found is to follow the machine learning community on Twitter. Keeping track of advancements in AI is not only fun but will also help in interviews by demonstrating to hiring managers your investment in the field. To get you started following the machine learning community, here's a fairly extensive list of AI researchers and pioneers I'm following.

Neural networks, machine learning, artificial intelligence – I get the impression that these slogans attack us from everywhere. They are mainly associated with the giants of the IT industry, who from time to time report spectacular progress in this field. I decided to dispel myths about machine learning using a series of articles explaining this problem by interesting examples. In this article, I will show you how to build and learn a neural network to generate one image based on another step by step. In this guide we will create a neural network, which we will put the task of transforming one image into another.

The SA Innovation Summit as an annual flagship event on the South African Innovation Calendar, is a platform for nurturing, developing and showcasing African innovation, as well as facilitating innovation thought-leadership. Created to support and promote innovation and facilitate collaboration within its own eco-system, the initiative brings together corporates, thought leaders, inventors, entrepreneurs, academia and policy makers to amplify South Africa's renowned competitive edge and to inspire sustained economic growth across the continent of Africa. The outcomes achieved by the Summit, is a powerful platform to bring together thought leaders and accelerate innovation in South Africa, and into the African continent as whole. MIIA ill also be represented at the South African Innovation Summit and invitethe MIIA community to also join the 48-hour hackathon being held in Cape Town Stadium from 5 - 7 September 2017.

Have you ever done things that were fun and easy instead of a really hard and really important thing that you really had to do? You know, like sorting through 10-year-old pictures and reordering them in new files with improved -- and more creative -- names, instead of doing that major spring cleaning of the house that you have planned for two months in advance. According to TED speaker and procrastinator expert Tim Urban from Whait But Why (a website that I've stumbled upon during a procrastination session), all people are procrastinators! You and everyone you know are procrastinators. Some are more pro than others, though.

In this tutorial, you will learn how to use OpenCV to perform face recognition. To build our face recognition system, we'll first perform face detection, extract face embeddings from each face using deep learning, train a face recognition model on the embeddings, and then finally recognize faces in both images and video streams with OpenCV. Today's tutorial is also a special gift for my fiance e, Trisha (who is now officially my wife). Our wedding was over the weekend, and by the time you're reading this blog post, we'll be at the airport preparing to board our flight for the honeymoon. To celebrate the occasion, and show her how much her support of myself, the PyImageSearch blog, and the PyImageSearch community means to me, I decided to use OpenCV to perform face recognition on a dataset of our faces. You can swap in your own dataset of faces of course! All you need to do is follow my directory structure in insert your own face images. As a bonus, I've also included how to label "unknown" faces that cannot be classified with sufficient confidence. To learn how to perform OpenCV face recognition, just keep reading!

The trends in entertainment are usually a very accurate measure of what'tickles the pickle' of people at a certain time. In the ancient world, people enjoyed gladiator fights or (pretty much at the opposite end) skillfully written plays. In the'roaring twenties' entertainment meant basically lush, shiny parties with loud music and no small amount of alcohol and other substances. Once the motion picture appeared that became the beacon of leisure and fun. Hollywood gave and is still producing both heartwarming and heart-stopping experiences. Judging by box office results, the success of movies as a favorite pastime is still on the rise.

How is your organization preparing for artificial intelligence (AI)? Ask this question of businesses investing in this field today, and the answer almost always comes down to "data"-- with leaders talking about "data preparations" or "data science talent acquisition." Related: Which Countries Are Ready for AI Adoption? While there would be no AI without data, enterprises that fail to ready the other side of the equation-- people-- don't just stunt their capacity for good AI, they risk sunk investment and jeopardize employee trust, brand backlash or worse. After all, people are the ones building, measuring, consuming and determining the success of AI in enterprise and consumer settings.

The long and confusing set of numbers that follow every WiFi name is finally disappearing. And it is being swapped for something far more simple. Anyone who has ever tried to buy a WiFi device has probably struggled with the arcane naming system that each of them is given. Each begins with 802.11, and then is followed by letters like "ac" – it's those letters that matter, but it can be hard to work out how and why. The codes actually refer to something very useful: different generations of WiFi technology, which bring with them upgrades and updates to things like the speed they can transmit data.

Helsinki University is offering a free online Artificial Intelligence course in English to anyone, anywhere. This free Artificial Intelligence (AI) online course is made for non-technical people so no special knowledge or skills are needed to take the course. AI is embedded in so many part of our lives - this course is meant to dispel any mystery around the technology that AI uses, the impact it has on our lives and how AI will develop in the coming years. Do you wonder what AI really means? Are you thinking about the kind of impact AI might have on your job or life?

This post is a token of appreciation for the amazing open source community of Data Science, to which I owe a lot of what I have learned. For last few months, I have been working on a side project of mine to develop machine learning application on streaming data. It was a great learning experience with numerous challenges and lots of learning, some of which I have tried to share in here. This post is focused on how to deploy machine learning models on streaming data and covers all 3 necessary areas of a successful production application: infrastructure, technology, and monitoring. The first step for any successful application is to determine the technology stack in which it should be written, on the basis of business requirements. As a general rule, when the amount of data is huge, use Spark.