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Java Deep Learning Cookbook - Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j (Paperback)
Loot Price: R1,160
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Java Deep Learning Cookbook - Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j (Paperback)
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Use Java and Deeplearning4j to build robust, scalable, and highly
accurate AI models from scratch Key Features Install and configure
Deeplearning4j to implement deep learning models from scratch
Explore recipes for developing, training, and fine-tuning your
neural network models in Java Model neural networks using datasets
containing images, text, and time-series data Book DescriptionJava
is one of the most widely used programming languages in the world.
With this book, you will see how to perform deep learning using
Deeplearning4j (DL4J) - the most popular Java library for training
neural networks efficiently. This book starts by showing you how to
install and configure Java and DL4J on your system. You will then
gain insights into deep learning basics and use your knowledge to
create a deep neural network for binary classification from
scratch. As you progress, you will discover how to build a
convolutional neural network (CNN) in DL4J, and understand how to
construct numeric vectors from text. This deep learning book will
also guide you through performing anomaly detection on unsupervised
data and help you set up neural networks in distributed systems
effectively. In addition to this, you will learn how to import
models from Keras and change the configuration in a pre-trained
DL4J model. Finally, you will explore benchmarking in DL4J and
optimize neural networks for optimal results. By the end of this
book, you will have a clear understanding of how you can use DL4J
to build robust deep learning applications in Java. What you will
learn Perform data normalization and wrangling using DL4J Build
deep neural networks using DL4J Implement CNNs to solve image
classification problems Train autoencoders to solve anomaly
detection problems using DL4J Perform benchmarking and optimization
to improve your model's performance Implement reinforcement
learning for real-world use cases using RL4J Leverage the
capabilities of DL4J in distributed systems Who this book is forIf
you are a data scientist, machine learning developer, or a deep
learning enthusiast who wants to implement deep learning models in
Java, this book is for you. Basic understanding of Java programming
as well as some experience with machine learning and neural
networks is required to get the most out of this book.
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