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Key benefits

Go beyond the theory and put Deep Learning into practice with Java

*Find out how to build a range of Deep Learning algorithms using a range of leading frameworks including DL4J, Theano and Caffe

Whether you’re a data scientist or Java developer, dive in and find out how to tackle Deep Learning

Description

AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI, being able to tackle Deep Learning is going to a vital and valuable skill not only within the tech world but also for the wider global economy that depends upon knowledge and insight for growth and success. It’s something that’s moving beyond the realm of data science – if you’re a Java developer, this book gives you a great opportunity to expand your skillset. Starting with an introduction to basic machine learning algorithms, to give you a solid foundation, Deep Learning with Java takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. Once you’ve got to grips with the fundamental mathematical principles, you’ll 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 apply Deep Learning to a range of real-world use cases. Featuring further guidance and insights to help you solve challenging problems in image processing, speech recognition, language modeling, this book will make you rethink what you can do with Java, showing you how to use it for truly cutting-edge predictive insights. As a bonus, you’ll also be able to get to grips with Theano 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. Wherever you’ve come from – whether you’re a data scientist or Java developer – you will become a part of the Deep Learning revolution!

What you will learn

* Get a practical deep dive into machine learning and deep learning algorithms

* Implement machine learning algorithms related to deep learning

* Explore neural networks using some of the most popular Deep Learning frameworks

* Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms

* Discover more deep learning algorithms with Dropout and Convolutional Neural Networks

* Gain an insight into the deep learning library DL4J and its practical uses

* Get to know device strategies to use deep learning algorithms and libraries in the real world

* Explore deep learning further with Theano and Caffe

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Frequently bought together

Mastering Concurrency Programming with Java 8

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Amazon verified reviews

Luigi Cardarella Nov 10, 2016

Bel libro che spiega proprio bene il deep learning e finalmente degli esempi con Dl4j.Veramente bello.Lo consiglio vivamente a chi vuole sviluppare o semplicemente curiosare in questo fantastico mondo del deep learning con java.

Amazon Verified review

Sujit Pal Jun 17, 2016

I thought this was a very well-written book on Deep Learning (DL). Java is (in my opinion) not the best language for teaching algorithms, but the example code is very readable. Like many DL books, the book focuses a lot on basic concepts and the math derivations behind them, so in that sense it is relatively undifferentiated from these books - however, it is is the only one that does so in Java. This is the only book I have read that has extensive coverage of pre-training (Deep Belief Networks, Restricted Boltzmann Machines, Denoising Autoencoders (DA), and Stacked DAs). Other "standard" networks such as Multilayer Perceptrons, Convolutional Neural Networks and Recurrent Neural Networks are also covered, about as well as other books I have read. The author provides good intuition around ideas such as dropout and learning rate adjustments. I bought the book because I wanted a quick intro to the DeepLearning4j framework - unfortunately the book has only one chapter dedicated to that with a fairly basic example. However, one can use it as a template and refer to the (very informative) DL4j website for more information. Overall, I think it is a good resource for Java programmers who want to learn Deep Learning.

Xidong Wu May 16, 2017

As a software engineer, I have read several theoretical books to try to understand the concepts of deep learning. I found it was really difficult for me to truly grasp the concepts such as DBN and CNN. After having gone through this book and read line by line the code provided, I can declare that I am a deep learning expert now.

Kindle Customer May 26, 2017

Good examples and starting points. Provides a good history and multiple language examples. Recommend as a starting point. Useful resources.

Amazonのお客様 Jun 23, 2016

I'm at mid-level for deep learning and was looking for a book I could go through the whole picture from the theory to implementation.I think this is what I needed.For the next step, I want a book which goes further implementations and coding.

Java Deep Learning Essentials: Unlocking the next generation of predictive power

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