dive into the future of data science and learn how to build the sophisticated algorithms that are fundamental to deep learning and AI with Java Sugomori, Yusuke creator author. text enk 2016 monographic eng spa

Electronic resource

1 online resource (1 volume) : illustrations. Go beyond the theory and put Deep Learning into practice with JavaFind out how to build a range of Deep Learning algorithms using a range of leading frameworks including DL4J, Theano and CaffeWhether you're a data scientist or Java developer, dive in and find out how to tackle Deep LearningWho This Book Is ForThis book is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It would also be good for machine learning users who intend to leverage deep learning in their projects.What You Will LearnGain a practical understanding of machine learning and deep learning algorithmsImplement machine learning algorithms related to deep learningExplore neural networks using some of the most popular deep learning frameworksDive into Deep Belief Nets and Stacked Denoising Autoencoder algorithmsDiscover more deep learning algorithms with Dropout and Convolutional Neural NetworksGain an insight into the deep learning library DL4J and its practical usesGet to know device strategies in order to use deep learning algorithms and libraries in the real worldExplore deep learning further with Theano, TensorFlow, and CaffeIn DetailAI and deep learning are transforming the way we understand software, making computers more intelligent. Deep learning algorithms are being used across a broad range of industries, moving beyond the realm of data science.Starting with an introduction to basic machine learning algorithms, Java Deep Learning Essentials takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. You'll then start exploring neural networks and identify how to tackle challenges in large networks using advanced algorithms. You will learn how to use the DL4J library and solve challenging problems in image processing, speech recognition, and language modeling. You'll also get to grips with Theano, TensorFlow, and Caffe, two of the most important tools in deep learning today. By the end of the book, you'll be ready to tackle deep learning with Java and become a part of the deep learning revolution! Chapter 1: Deep Learning Overview -- Chapter 2: Algorithms for Machine Learning – Preparing for Deep Learning -- Chapter 3: Deep Belief Nets and Stacked Denoising Autoencoders -- Chapter 4: Dropout and Convolutional Neural Networks -- Chapter 5: Exploring Java Deep Learning Libraries – DL4J, ND4J, and More -- Chapter 6: Approaches to Practical Applications – Recurrent Neural Networks and More -- Chapter 7: Other Important Deep Learning Libraries -- Chapter 8: What's Next? -- Index. Yusuke Sugomori. Includes index. Includes bibliographical references and index. Java (Computer program language) Machine learning Application software Development QA76.73 .J38 S846 2016 9781785283147 1785283146 CL0500000750 Safari Books Online http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1243158&site=ehost-live http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1243158&site=ehost-live UMI 160623 20170712145949.0 12866052 eng