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. ...