After adding DL4J core dependency and ND4J dependencies, as mentioned in step 1 and step 2, we are able to create neural networks. In step 2, the ND4J maven configuration is mentioned as a necessary backend dependency for Deeplearnign4j. ND4J is the scientific computation library for Deeplearning4j.
ND4J is a scientific computing library written for Java, just like NumPy is for Python.
Step 3 is very crucial for the ETL process: that is, data extraction, transformation, and loading. So, we definitely need this as well in order to train the neural network using data.
Step 4 is optional but recommended, since logging will reducee the effort involved in debugging.