Two new training provider partnerships are exploring the possibility of using artificial intelligence (AI) to help. Last month, Mandel Communications announced a partnership with Orai on a free communication coaching app that uses AI to provide instant feedback on speech, including clarity, the use of filler words, pacing and energy. This feedback is based on computational linguistics research and a data set of, according to co-founder Danish Dhamani, "thousands of people with different accents, different languages … speaking across the world." The app also includes Mandel's communication skills training and the ability to send recordings to users' managers and coaches for continued development. The company also offers the ability to create custom content for a company's specific messaging.

Developing deep learning applications just got even simpler and faster. In this session, you will learn how to program deep learning models using Gluon, the new intuitive, dynamic programming interface available for the Apache MXNet open-source framework. We'll also explore neural network architectures such as multi-layer perceptrons, convolutional neural networks (CNNs) and LSTMs.

The basic fact is that technology eliminates jobs, not work. It is the continuous obligation of economic policy to match increases in productive potential with increases in purchasing power and demand. Otherwise the potential created by technical progress runs to waste in idle capacity, unemployment, and deprivation. The fear that machines will replace human labor is a durable one in the public mind, from the time of the Luddites in the early 19th century. Yet most economists have viewed "the end of humans in jobs" as a groundless fear, inconsistent with the evidence.

Note: Some of these courses are free. But if you decide to purchase anything (using the links below) you'll be financially supporting the Personal Growth publication. This course will give you a full overview of the Data Science journey. You'll develop a good understanding of SQL, SSIS, Tableau, and Gretl. This course begins with Tableau basics.

Each Summit offers a comprehensive overview of a specific game industry discipline, and the AI Summit is no exception. This year, for example, Guerrilla Games' Julian Berteling will be delivering a very cool talk on "Beyond'Killzone': Creating New AI Systems for'Horizon Zero Dawn'" to explain the changes that Guerilla made to switch from having to support a single human enemy in closed corridor spaces to a game with more than 25 wildly different characters in a large open world. You'll want to see this, because attendees will learn ways of dealing with an expanding scope of AI, either throughout a single title's production or when moving to a new title. Additionally, attendees will understand concrete methods for dealing with navigation, movement, and animation for open world titles with many, widely varied agents. And in her Summit session on "'Race for the Galaxy': A Neural Network in Production" Temple Gate chief Theresa Duringer will explain how the studio's game Race for the Galaxy (a digital adaptation of the board game) uses temporal difference learning to power its AI.

Recently I wrote about the growing importance of investing in the skills of employees so that they can adapt to the changing technology landscape they're working in. It was based upon a recent Accenture report, which argued that organizations need to take a systemic approach to ensuring the interaction between man and machine is a smooth one. Whilst generally corporate training budgets are on a downward trend, there are a couple of recent developments that suggest all is not entirely lost and small progress is being made. The first comes from Google, who have teamed up with MOOC pioneer Coursera to launch an online course for IT support professionals. It's estimated that IT support roles will grow by 10% by 2026, and the course is designed to learn the kind of skills required to land such a role.

Google is opening a university in California to train African-American computer science majors in intensive coding instruction. Josh King has the story (@abridgetoland). Google is opening up the Howard West program to 100 students from Howard and other historically black universities and colleges for a full academic year starting this fall. SAN FRANCISCO -- Last summer, Howard University dispatched 26 students to Google's Mountain View, Calif., campus for an intensive 12-week course on coding. The experimental test run boosted students' technical chops and their confidence, and now -- starting in the fall -- the Internet giant is opening the program to 100 students from Howard and other historically black colleges and universities for a full academic year.

I played around with it in 2016 but seemingly all of the API has changed since then. Additionally, Eager seems to be the new hot thing. I have experience with Keras and PyTorch but I find the tutorials on the TF website somewhat lacking. Does anyone have a pointer to some good tutorials that use all the new (at least to me) features like Estimators and Datasets?

"This course has taught me many things I wanted to know about pandas. It covers everything since the installation steps, so it is very good for anyone willing to learn about data analysis in python /jupyter environment." "Good explanation, I have laready used two online tutorials on data -science and this one is more step by step, but it is good" "i have studied python from other sources as well but here i found it more basic and easy to grab especially for the beginners. I can say its best course till now . The average data scientist today earns $130,000 a year by glassdoor.

Last year we announced that we were developing a new deep learning course based on Pytorch (and a new library we have built, called fastai), with the goal of allowing more students to be able to achieve world-class results with deep learning. Today, we are making this course, Practical Deep Learning for Coders 2018, generally available for the first time, following the completion of a preview version of the course by 600 students through our diversity fellowship, international fellowship, and Data Institute in-person programs. The only prerequisites are a year of coding experience, and high school math (math required for understanding the material is introduced as required during the course). The course includes around 15 hours of lessons and a number of interactive notebooks, and is now available for free (with no ads) at course.fast.ai. Our research focuses on how to make practically useful deep learning more widely accessible. Often we've found that the current state of the art (SoTA) approaches aren't good enough to be used in practice, so we have to figure out how to improve them.