Chollet François, Allaire J.J. Deep Learning with R

Manning Publications, 2018. — 392 p.Artificial intelligence has made some incredible leaps. Deep learning systems now deliver near-human speech and image recognition, not to mention machines capable of beating world champion Go masters. Deep learning applies to a widening range of problems, such as question answering, machine translation, and optical character recognition. It’s behind photo tagging, self-driving cars, virtual assistants and other previously impossible applications.In the past few years, artificial intelligence (AI) has been a subject of intense media hype. Machine learning, deep learning, and AI come up in countless articles, often outside of technology­minded publications. We’re promised a future of intelligent chatbots, self­driving cars, and virtual assistants - a future sometimes painted in a grim light and other times as utopian, where human jobs will be scarce, and most economic activity will be handled by robots or AI agents. For a future or current practitioner of machine learning, it’s important to be able to recognize the signal in the noise so that you can tell world­changing developments from overhyped press releases. Our future is at stake, and it’s a future in which you have an active role to play: after reading this book, you’ll be one of those who develop the AI agents. So let’s tackle these questions: What has deep learning achieved so far? How significant is it?