Deep Machine Learning

Abstract

With deep learning technology, machine learning has shown impressive results. Nonetheless, these techniques frequently use excessive amounts of resources; they demand big datasets, a lot of parameters, and a lot of processing power. In order to develop machine learning models that are efficient with resources, the authors have outlined a general machine learning technique in this work that they call deep machine learning. All the methods that initially identify inductive biases and then use those inductive biases to improve the learning efficiency of models come under the umbrella of deep machine learning. Numerous robust machine learning techniques are currently in use, and some of them are highly well-liked precisely because of their efficacy. Deep machine learning, however, is still in its infancy, and much more work remains. The efforts must be focused in order to progress artificial intelligence (AI).