RApid DEvelopment of Neural Networks (RADENN)
RADENN is a domain-specific language written in Python 3.x for the rapid development of fully connected neural networks for classification and regression problems. RADENN is intended to be used by Data Scientists, Data Analysts, Big Data Engineers, or any person who needs a quick way to create prototypes and models, even without extensive knowledge of programming or deep learning.
Data Types and Variable Declaration
There are 13 built-in data types in RADENN divided into two groups, the general data types, and the specific data types:
As their name indicates, the general data types have a general-purpose, including common data types like numbers and strings found in most programming languages. It is worth mentionting that booleans can be defined, but they are not considered data types since internally, they are interpreted as numbers where false=0 and true=1. On the other hand, the specific data types are oriented to facilitate the definition, training and evaluation of neural networks.