使用最新的Java深度学习库构建和部署功能强大的神经网络模型
Build and deploy powerful neural network models using the latest Java deep learning libraries
主要特点
*通过实现现实世界的项目来理解基于Java的DL
*掌握各种ANN模型的实现，并建立自己的DL系统
*使用NLP、图像分类、RL和GPU处理开发应用程序
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
Java是应用最广泛的编程语言之一。随着深度学习的兴起，它已成为数据科学家和机器学习专家的热门工具选择。
Java深度学习项目首先概述深度学习概念，然后深入研究高级项目。您将了解如何使用不同的深度神经网络架构构建多个项目，如多层感知器、深度信念网络、CNN、LSTM和因式分解机。
您将熟悉流行的Java深度学习库和机器学习库，如Deeplearning4j、Spark-ML和RankSys，您将能够使用它们的特性在分布式计算环境中构建和部署项目。
然后，您将使用Java生态系统探索高级领域，如迁移学习和深度强化学习，以一种简单易懂的方式涵盖各种现实领域，如医疗保健、NLP、图像分类和多媒体分析。专家评论、提示将在每个项目中给予见解和说明。
到本书结束时，您将提高您在Java中进行深度学习的专业知识，使其超越理论，并能够构建自己的高级深度学习系统。
Book Description
Java 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.
你将学到什么
-掌握深度学习和神经网络结构
-使用DL4J和开源API构建涵盖图像分类、对象检测、在线交易、迁移学习和多媒体分析的真实应用程序
-训练ML代理使用深度强化学习从数据中学习
-使用因子分解机进行高级电影推荐
-使用Spark和DL4J在分布式GPU上训练DL模型以加快深度学习
-通过69个常见问题解答，让您的学习体验更轻松
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
如果您是数据科学家、机器学习专业人士或深度学习实践者，希望通过深入研究Java深度学习的实际应用来扩展您的知识，那么这本书就是您所需要的！准备好建立先进的深度学习模型来进行复杂的数值计算。使用本书需要对机器学习概念有一些基本的了解，并具备Java的基本知识。
Who This Book Is For
If 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.