LUDWIG: A Type-Based Declarative Deep Learning Toolbox

The overriding goal is to make ML methods easy to use and/or construct, which is especially important in the context of complex applications. In this article, we will have a look into what declarative learning is and how a Toolbox called Ludwig built by UberAI can be used in the context of it. The major points to be discussed in this article are listed below. Let's start the discussion by understanding what declarative learning is in machine learning. Declarative ML intends to simplify the usage and/or creation of ML algorithms by isolating application or algorithm semantics from the underlying data representations and execution plans, resulting in a high-level definition of ML tasks or algorithms.