You're reading from Java Deep Learning Cookbook

Product typeBook

Published inNov 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781788995207

Edition1st Edition

Languages

Java

Tools

Deeplearning4j TensorFlow

Concepts

Deep Learning

Author (1)

Rahul Raj

DL4J/ND4J-specific configuration

Apart from general benchmarking guidelines, we need to follow additional benchmarking configurations that are DL4J/ND4J-specific. These are important benchmarking configurations that target the hardware and mathematical computations.

Because ND4J is the JVM computation library for DL4J, benchmarks mostly target mathematical computations. Any benchmarks discussed with regard to ND4J can then also be applied to DL4J. Let's discuss DL4J/ND4J-specific benchmarks.

Getting ready

Make sure you have downloaded cudNN from the following link: https://developer.nvidia.com/cudnn. Install it before attempting to configure it with DL4J. Note that cuDNN doesn't come as a bundle with CUDA. So...

The rest of the page is locked

You have been reading a chapter from

Java Deep Learning Cookbook

Published in: Nov 2019Publisher: PacktISBN-13: 9781788995207

Author (1)

Rahul Raj

Rahul Raj has more than 7 years of IT industry experience in software development, business analysis, client communication, and consulting on medium-/large-scale projects in multiple domains. Currently, he works as a lead software engineer in a top software development firm. He has extensive experience in development activities comprising requirement analysis, design, coding, implementation, code review, testing, user training, and enhancements. He has written a number of articles about neural networks in Java and they are featured by DL4J/ official Java community channels. He is also a certified machine learning professional, certified by Vskills, the largest government certification body in India.
Read more about Rahul Raj

Other recommended products

Related to this chapter

Hands-On Deep Learning with Apache Spark

Deep Learning is a subset of Machine Learning where data sets with several layers of complexity can be processed. This book teaches you the different techniques using which deep learning solutions can be implemented at scale, on Apache Spark. This will help you gain experience of implementing your deep learning models in many real-world use cases.

BookJan 2019322 pages

Java Deep Learning Projects

You will build full-fledged, deep learning applications with Java and different open-source libraries. Master numerical computing, deep learning, and the latest Java programming features to carry out complex advanced tasks. This book is filled with best practices/tips after every project to help you optimize your deep learning models with ease.

BookJun 2018436 pages

Java for Data Science

Harness the incredible power of Java-based approaches to data science and create new, innovative applications to explore, visualise and analyse big data. With its tutorial approach and step-by-step instructional style, Java for Data Science is the ultimate data science book for Java developers interested in Java-based data science solutions.

BookJan 2017386 pages

Deep Learning with Hadoop

BookFeb 2017206 pages

Hands-On Java Deep Learning for Computer Vision

This book will take you through the process of efficiently training deep neural networks in Java for Computer Vision-related tasks. You will build real-world applications ranging from simple Java handwritten digit recognition models to real-time autonomous car driving systems and face recognition models using the popular Java-based libraries.

BookFeb 2019260 pages

Mastering Java for Data Science

Java is the most wide-spread programming language nowadays, and you fill find it everywhere, from small startup companies to large enterprises. It is also a common choice for developing Data Science applications thanks to Java's prevalence and rich data processing toolbox. This book will explain how to use Java for Data Science, overview the available Machine Learning libraries, and cover many topics including supervised and unsupervised learning, natural language processing, deep learning, and big data

BookApr 2017364 pages

Personalised recommendations for you

Based on your interests and search pattern

Et al.

Ever wonder why speech recognition systems don't understand the Scottish accent, or what would happen if an astronaut only ate mac 'n' cheese, or other spurious reflections you'd have at a bar? We did, then collated those deliberations into absurd research articles with fake figures and methodologies inspired by even more fictionally absurd studies.

BookAug 2023230 pages5

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages4

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages5

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages1

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages5

Mastering Tableau 2023

This book is a comprehensive resource to mastering your Tableau skills and becoming a BI expert. As you progress, you will learn how to build advanced dashboards and improve your storytelling to derive key business insight, as well as make you well-versed with advanced functionalities of Tableau in the business intelligence domain.

BookAug 2023684 pages

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

BookSep 2023258 pages5

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

BookSep 2023258 pages2

Data Engineering with AWS

Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.

BookOct 2023636 pages5

Modern Data Architecture on AWS

Every organization wants an agile, performant, and cost-effective data platform that meets all their current and future business needs. Purpose-built AWS analytics services and their features play a big part in building such a modern data platform. This book brings to you all the design and architectural patterns that’ll help you achieve this goal.

BookAug 2023420 pages5

Practical Guide to Applied Conformal Prediction in Python

Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.

BookDec 2023240 pages

TinyML Cookbook

With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. It provides a comprehensive understanding of the theoretical foundations while giving you hands-on experience training ML models for deployment on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano microcontrollers.

BookNov 2023664 pages

You're reading from Java Deep Learning Cookbook

Unlock this book and the full library FREE for 7 days

Author (1)

Hands-On Deep Learning with Apache Spark

Java Deep Learning Projects

Java for Data Science

Deep Learning with Hadoop

Hands-On Java Deep Learning for Computer Vision

Mastering Java for Data Science

Et al.

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Mastering Tableau 2023

Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

Data Engineering with AWS

Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.

Modern Data Architecture on AWS

Practical Guide to Applied Conformal Prediction in Python

Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.

TinyML Cookbook