At the college level eSports are set to explode as more school-supported programs sprout up every day. But officially sanctioned high school esports are essentially nonexistent. Many teachers (and parents) still see video games as a waste of time. Teens looking for competitive team play could previously only find it in the unsung volunteer efforts of online leagues. They've been making do on their own for years, but they can't offer meeting spaces to practice and connect, or validation from adults and authority figures. Yet in the last several months, a trio of local leagues have debuted that are fully affiliated with high schools and supported by education districts.

Laura was born in a small town in North Carolina. She went on to earn a B.S. in Textile Engineering and a B.A. in Spanish at North Carolina State University. Laura thought this unique combination of majors would be amazing after attending a summer camp in high school where she played with bouncing polymers. While attending North Carolina State University, she earned a scholarship to study a summer term in Peru, where she fell in love with the Spanish language. Upon graduation, she moved to Washington, D.C. where she served in a variety of digital information roles.

I grew up in a small town in Transylvania, and will always remember the day when I assembled my first computer and loaded the first mp3 songs and movies on it. At the time we didn't yet have Internet in my home, and I was exchanging files via CDs with my friends and my father's colleagues. By the time I went to college, my campus had its own intranet, and my friends and I built up a collection of hundreds of albums, television series, movies, software packages, anything you could imagine. It was as if all of the students were part of this giant web, seeding and peering on torrents while constantly exchanging the latest school news in forums and chat rooms. Later, I used the internet to find my first internship abroad, master's scholarship, job, and apartment.

Natural Language Processing is used in many applications to provide capabilities that were previously not possible. It involves analyzing text to obtain the intent and meaning, which can then be used to support an application. Using NLP within an application requires a combination of standard Java techniques and often specialized libraries frequently based on models that have been trained. If you're interested to learn the powerful Natural Language Processing techniques with Java, then go for this Learning Path. Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

Artificial Intelligence is a fascinating topic and also a kind of buzzword which has been there for years and will dominate for many more years. As and when I interact with developers and students I hear different intuitions about machine learning, deep learning and AI. Sometimes, there's also a confusion whether AI, ML & DL are all the same or different from each other. So, I use this infographic in my first slide of a presentation. As humans, we all are different and our way of learning is also differs.

Machine learning is enabling computers to tackle tasks that have, until now, only been carried out by people. The next wave of IT innovation will be powered by artificial intelligence and machine learning. We look at the ways companies can take advantage of it and how to get started. From driving cars to translating speech, machine learning is driving an explosion in the capabilities of artificial intelligence -- helping software make sense of the messy and unpredictable real world. But what exactly is machine learning and what is making the current boom in machine learning possible? At a very high level, machine learning is the process of teaching a computer system how to make accurate predictions when fed data.

This course will get you started in building your FIRST artificial neural network using deep learning techniques. Following my previous course on logistic regression, we take this basic building block, and build full-on non-linear neural networks right out of the gate using Python and Numpy. All the materials for this course are FREE. We extend the previous binary classification model to multiple classes using the softmax function, and we derive the very important training method called "backpropagation" using first principles. I show you how to code backpropagation in Numpy, first "the slow way", and then "the fast way" using Numpy features.

Machine learning is a way for a program to analyze previous data (or past experiences) to make decisions or predict the future. Wow, that sounds pretty complex! But aren't you claiming everyone can do it? We use frameworks like TensorFlow that make it easy to build, train, test, and use machine learning models. All you need to know is a little Python, which we will teach you, of course. TensorFlow has really been a saving grace.

The business world is changing, there's no doubt about it. And with that, so is business education. With globalization, technological advancements and demographic changes, the future of business will look vastly different than it does today. Margaret Andrews, a contributor at Inside Higher Ed, recently discussed how business schools can adapt to this change and best prepare students for the future of business. Creativity will become one of the top three skills workers will need to succeed, according to the World Economic Forum's report, "The Future of Jobs," which analyzes the employment, skills and workforce strategy for the future.

The Carnegie Mellon School of Computer Science (SCS) has launched the first undergraduate degree in artificial intelligence (AI) in the United States. Starting Autumn 2018, the program appears fittingly rigorous, accepting a total of only 100 students a year. First years can only declare themselves AI majors in the spring, after completing core mathematics and computer science classes in the SCS. The 100 second-, third- and fourth-year students who make it onto the programme will take additional courses in statistics and probability, computational modeling, machine learning and symbolic computation. The degree will also involve an emphasis on ethics and social responsibility, as part of the SCS' desire to use AI to improve social conditions.