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Java Deep Learning Projects - Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs (Paperback)
Loot Price: R1,465
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Java Deep Learning Projects - Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs (Paperback)
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Build and deploy powerful neural network models using the latest
Java deep learning libraries Key Features Understand DL with Java
by implementing real-world projects Master implementations of
various ANN models and build your own DL systems Develop
applications using NLP, image classification, RL, and GPU
processing Book DescriptionJava is one of the most widely used
programming languages. With the rise of deep learning, it has
become a popular choice of tool among data scientists and machine
learning experts. Java Deep Learning Projects starts with an
overview of deep learning concepts and then delves into advanced
projects. You will see how to build several projects using
different deep neural network architectures such as multilayer
perceptrons, Deep Belief Networks, CNN, LSTM, and Factorization
Machines. You will get acquainted with popular deep and machine
learning libraries for Java such as Deeplearning4j, Spark ML, and
RankSys and you'll be able to use their features to build and
deploy projects on distributed computing environments. You will
then explore advanced domains such as transfer learning and deep
reinforcement learning using the Java ecosystem, covering various
real-world domains such as healthcare, NLP, image classification,
and multimedia analytics with an easy-to-follow approach. Expert
reviews and tips will follow every project to give you insights and
hacks. By the end of this book, you will have stepped up your
expertise when it comes to deep learning in Java, taking it beyond
theory and be able to build your own advanced deep learning
systems. What you will learn Master deep learning and neural
network architectures Build real-life applications covering image
classification, object detection, online trading, transfer
learning, and multimedia analytics using DL4J and open-source APIs
Train ML agents to learn from data using deep reinforcement
learning Use factorization machines for advanced movie
recommendations Train DL models on distributed GPUs for faster deep
learning with Spark and DL4J Ease your learning experience through
69 FAQs Who this book is forIf you are a data scientist, machine
learning professional, or deep learning practitioner keen to expand
your knowledge by delving into the practical aspects of deep
learning with Java, then this book is what you need! Get ready to
build advanced deep learning models to carry out complex numerical
computations. Some basic understanding of machine learning concepts
and a working knowledge of Java are required.
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