I'm going to start this post by saying that it makes no sense for anyone to pay management fees to get a return stream that… The Ideal ETF Most investors choose an ETF to act on a market view -- gold will rise, U.S. equities will fall, and so on.

IoT is one of the transformational trends that will shape the future of businesses in 2017 and beyond. Many firms see big opportunity in IoT uses and enterprises start to believe that IoT holds the promise to enhance customer relationships and drive business growth by improving quality, productivity, and reliability on one side, and on the other side reducing costs, risk, and theft. By having the right IoT model companies will be rewarded with new customers, better insights, and improved customer satisfaction to mention few benefits. With all this in mind, let's explore some of the trends of IoT impacting business and technology in 2017: Blockchain is more than a concept now and has applications in many verticals besides FinTech including IoT. Blockchain technology is considered by many experts as the missing link to settle scalability, privacy, and reliability concerns in the Internet of Things.

Researchers from Google's DeepMind division say they have shown how their differentiable neural computer is able to process information using so-called'slow' thinking thought processes. Researchers are successfully teaching machines to process information in ways that emulate the subtleties and complexities of human thought processes.

This is a hands-on guide to machine learning for programmers with no background in AI. Using a neural network doesn't require a PhD, and you don't need to be the person who makes the next breakthrough in AI in order to use what exists today. What we have now is already breathtaking, and highly usable. I believe that more of us need to play with this stuff like we would any other open source technology, instead of treating it like a research topic. In this guide our goal will be to write a program that uses machine learning to predict, with a high degree of certainty, whether the images in data/untrained-samples are of dolphins or seahorses using only the images themselves, and without having seen them before. Here are two example images we'll use: To do that we're going to train and use a Convolutional Neural Network (CNN). We're going to approach this from the point of view of a practitioner vs. from first principles. There is so much excitement about AI right now, but much of what's being written feels like being taught to do tricks on your bike by a physics professor at a chalkboard instead of your friends in the park.

Fantastic resource created by Andrea Motosi. I've only included the 5 categories that are the most relevant to our audience, though it has 31 categories total, including a few on distributed systems and Hadoop. Click here to view the 31 categories. You might also want to check our our our internal resources (the first section below).

The beginning, or end, of every year is marked by an eruption of Top 10 lists. Permit me to start with my top pick, the annual Notre Dame Reilly Center Top 10 List of Ethical Dilemmas and Policy Issues in Science and Technology. Would you really want your car to do that? Forget about the prospect of your kids one day taking your keys away when you fail an eye or reflex test. And what happens if your car itself becomes a bit neurotic, consumed with your safety.

Pretty much all of the tech giants attend the vast Vegas expo - either to unveil new products or to clinch deals behind the scene. But in recent years it's been start-ups that have had many of the most eye-arresting and sensational reveals. There are more at this year's show than ever before, thanks in part to crowdfunding. They now have to convince retailers - hunting through the halls for the next bestsellers - that the promise of their concept videos has been delivered upon. Dozens of start-ups are also there thanks to help from governments and other national bodies - France, Israel, Ukraine and the Netherlands all have stands where they'll fly the flag for local talent.

Artificial intelligence has played a role in customer service for some time now, but it's only recently that its full potential for transforming the customer experience has come to light. Conversational commerce is redefining the role of messaging apps in customer engagement, while self-service tools continue to simplify the customer service process and shift the role of human customer service agents in the contact center. Here are six ways artificial intelligence is reshaping customer experiences of both the present and the future. Big data is a key player in targeted marketing practices, offering brands important insights into customer behavior. Artificial intelligence technology may interpret big data to identify customer browsing patterns, purchase history, recent access to customer devices, and most visited webpages.

This book serves as a comprehensive intermediate guide to programming in SQL using Python as a language. Every new programmer needs a reference guide to coding and programming as they learn the basics. The goal of this book is to allow for the reader to get a step by step, comprehensive guide to formulating and gaining new skills. In order to maintain and create a secure system, the importance of both security features to put in place, things to avoid and the basics of good communication with your system are three of the skills you should be able to master at an intermediate level by the end of this book. Within the pages of the book, I share with you the methods I have used to create and maintain websites both as I started my programming and coding journey--and I still use today.

Data science is fast becoming a critical skill for developers and managers across industries, and it looks like a lot of fun as well. But it's pretty complicated - there are a lot of engineering and analytical options to navigate, and it's hard to know if you're doing it right or where the bear traps lie. In this series we explore ways in to making sense of data science - understanding where it's needed and where it's not, and how to make it an asset for you, from people who've been there and done it. This InfoQ article is part of the series "Getting A Handle On Data Science" . You can subscribe to receive notifications via RSS. A lot of Machine Learning (ML) projects consist of fitting a (normally very complicated) function to a dataset with the objective of calculating a number like 1 or 0 (is it spam or not?) for classification problems or a set of numbers (e.g., weekly sales of a product) for regression ones.