eBook Details:
- Format: PDF and ePub
- Paperback: 436 pages
- Publisher: June 29, 2018
- Language: English
- ISBN-10: 178899745X
- ISBN-13: 978-1788997454
eBook Description:
Java Deep Learning Projects: Build and deploy powerful neural network models using the latest Java deep learning libraries
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.
- 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
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.
本站所有资源搜集于互联网,所提供下载链接也是站外链接,网站本身并不存储相关资源文件,如资源下载链接侵犯到版权方,请发送邮件到yufeiyohi@outlook.com,站长核实后会第一时间移除。