Mastering Deep Learning with Java
Uncover complex deep learning architectures and bring AI to your distributed JVM environment
Seiten
2019
Packt Publishing Limited (Verlag)
9781789132960 (ISBN)
Packt Publishing Limited (Verlag)
9781789132960 (ISBN)
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Implement and empower java applications with smart neural networks and specialized deep learning techniques
About This Book
* Build proficiency in CNN's and develop fully connected deep neural networks
*Explore advanced concepts of deep learning and know-how to plunge them into deep learning systems
*Implement deep learning models for causal reasoning and planning
Who This Book Is For
This book is for experienced Java programmers, data scientists, deep learning engineers and veteran statisticians who want to explore complex neural network architectures and uncover complex deep learning models for building high-precision predictive applications. You need to be well-versed with Java programming coupled with a basic experience in deep learning
What You Will Learn
* Know core aspects and issues in developing and deploying a Deep Learning model
*Learn Deep Learning architectures for various discriminative tasks such as classification and prediction
*Learn to visualize hidden states of a sequence model
*Explore the generative power of a simple sequence model
*Image generation task with Variational autoencoder
*Learn to address interpretability of model with a reinforcement learning agent
In Detail
Mastering Deep Learning with Java brings the utilization of the next-generation capability of deep neural nets and finding patterns in your datasets using powerful deep learning techniques. You will develop the capabilities to address complex deep learning situations using Java's popular and preferred libraries such as Deeplearning4j. You will not just learn but master neural network creation and NLP applications using libraries like Neuroph and CoreNLP. The latter section of the book will teach you to perform optimization of deep learning models with hyperparameters, cross-validation and various other methods to fix up problems faced with the accuracy and the speed of the models.
The book would also cover a couple of examples that would teach you how you can design optimized neural networks in the areas of computer vision, pattern recognition, robots and computer games. By the end of this book, you will be well equipped to utilize the complete capabilities of Java and its packages and would reinforce in strengthening the ingestion of deep learning in your java application
About This Book
* Build proficiency in CNN's and develop fully connected deep neural networks
*Explore advanced concepts of deep learning and know-how to plunge them into deep learning systems
*Implement deep learning models for causal reasoning and planning
Who This Book Is For
This book is for experienced Java programmers, data scientists, deep learning engineers and veteran statisticians who want to explore complex neural network architectures and uncover complex deep learning models for building high-precision predictive applications. You need to be well-versed with Java programming coupled with a basic experience in deep learning
What You Will Learn
* Know core aspects and issues in developing and deploying a Deep Learning model
*Learn Deep Learning architectures for various discriminative tasks such as classification and prediction
*Learn to visualize hidden states of a sequence model
*Explore the generative power of a simple sequence model
*Image generation task with Variational autoencoder
*Learn to address interpretability of model with a reinforcement learning agent
In Detail
Mastering Deep Learning with Java brings the utilization of the next-generation capability of deep neural nets and finding patterns in your datasets using powerful deep learning techniques. You will develop the capabilities to address complex deep learning situations using Java's popular and preferred libraries such as Deeplearning4j. You will not just learn but master neural network creation and NLP applications using libraries like Neuroph and CoreNLP. The latter section of the book will teach you to perform optimization of deep learning models with hyperparameters, cross-validation and various other methods to fix up problems faced with the accuracy and the speed of the models.
The book would also cover a couple of examples that would teach you how you can design optimized neural networks in the areas of computer vision, pattern recognition, robots and computer games. By the end of this book, you will be well equipped to utilize the complete capabilities of Java and its packages and would reinforce in strengthening the ingestion of deep learning in your java application
Ajit studied Computer Science at Indian Institute of Science, Bangalore, and Physics at Madras Christian College. He is a 2018 top writer at Quora where he contributes to topics such as Natural language processing, machine learning, artificial neural networks etc. His past time, which could be classified as typical if not boring is what keeps him going - visiting landmarks of human intellect and understanding them from a layman's perspective.
| Erscheint lt. Verlag | 31.5.2019 |
|---|---|
| Verlagsort | Birmingham |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| ISBN-13 | 9781789132960 / 9781789132960 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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