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Sunday, January 14, 2018

Learn To Build Your Own Neural Networks With This Training Bundle | Interesting Engineering - Innovation - AI

This is a promotional article about one of the company partners with Interesting Engineering. By shopping with us, you not only get the materials you need, but you’re also supporting our website.


IE Shop, The Interesting Engineering Shop features exclusive offers on the latest gadgets, software, and online courses hand-picked for Interesting Engineering readers inform, "Use TensorFlow and Theano to get a firm understanding of deep learning and artificial intelligence."

Photo: Pixabay

Science fiction movies seem to have done Artificial Intelligence (AI) a bit of a disservice. Due to decades of popular yet farfetched sci-fi releases, when most people think of AI, they think only of evil robots taking over the planet, or perhaps friendlier (but still evil, maybe?) robots along the lines of the robot-woman in Ex Machina.

In many ways, however, real-life artificial intelligence has become more interesting than in the movies, with self-driving cars redefining transportation, quantum computing reshaping how we work with large sets of data, and medical robots performing some of the most advanced surgeries known to man with astounding precision.

Indeed, the future of technology in many ways belongs to AI. This means that the most exciting and important careers of the future will belong to those who possess a solid understanding of both deep learning and artificial intelligence principles. The Deep Learning and Artificial Intelligence Introductory Bundle breaks down some of the more fascinating topics in these fields into easy-to-understand and entertaining lessons, and it’s on sale for just $39.

The first course in this bundle kicks off your education in this exciting field by giving you a deep understanding of probability theory—one of the most fundamental elements of deep learning and AI, since it allows for complex and accurate predictions to be made. You’ll learn about everything from Moore’s Law and linear regression to large-scale data analysis and beyond.


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