Deep Learning with R

Description 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. Its behind photo tagging, self-driving cars, virtual assistants and other previously impossible applications.   Deep Learning with R is for developers and data scientists with some R experience who want to use deep learning to solve real-world problems. The book is structured around a series of practical examples that introduce each new concept and demonstrate best practices. Youll begin by learning what deep learning is, how it connects with AI and Machine Learning, and why its rapidly gaining in importance right now. Youll then dive into practical applications of computer vision, natural language processing, and more.   Key features   Understand key machine learning concepts   Set up a computer environment for deep learning   Visualize neural networks   Use recurrent neural networks for text and sequence Classification   Audience Youll need intermediate R programming skills. No previous experience with machine learning or deep learning is required. About the technology Although deep learning can be a challenging subject, new technologies make it much easier to get started than ever before. The Keras deep learning library featured in this book puts ease of use and accessibility front and center, making it a great fit for new practitioners.