June 2018
Intermediate to advanced
436 pages
10h 33m
English
Content preview from Java Deep Learning Projects
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Preparing programming environment
In this section, we will discuss how to configure DL4J, ND4s, Spark, and ND4J before getting started with the coding. The following are prerequisites when working with DL4J:
- Java 1.8+ (64-bit only)
- Apache Maven for automated build and dependency manager
- IntelliJ IDEA or Eclipse IDE
- Git for version control and CI/CD
The following libraries can be integrated with DJ4J to enhance your JVM experience while developing your ML applications:
- DL4J: The core neural network framework, which comes up with many DL architectures and underlying functionalities.
- ND4J: Can be considered as the NumPy of the JVM. It comes with some basic operations of linear algebra. Examples are matrix creation, addition, and multiplication. ...