Java: Data Science Made Easy

Acquiring and manipulating data

The DL4J API has a number of techniques for acquiring data. We will focus on those specific techniques that we will use in our examples. The dataset used by a DL4J project is often modified using either binarization or normalization. Binarization converts data to ones and zeroes. Normalization converts data to a value between 1 and 0.

Data feed to DLN is transformed to a set of numbers. These numbers are referred to as vectors. These vectors consist of a one-column matrix with a variable number of rows. The process of creating a vector is called vectorization.

Canova (http://deeplearning4j.org/canova.html) is a DL4J library that supports vectorization. It works with many different types of datasets. It has ...