Automating the Creation of Machine Learning Algorithms using basic Math

The study of machine learning has progressed in several areas, including model structures and learning methodologies. The challenges of this research sparked the development of Auto ML, an area that tries to automate the building of Machine Learning algorithms by using basic mathematical operations as building blocks. This advancement on the other hand, has mostly concentrated on the architecture of deep neural networks. Introducing this novel framework leads to compensate the human intervention through a generic search space. A case in neural architecture search is a domain in which complex layers are used to automatically design neural networks. These modest accomplishments in creating ML algorithms from scratch, point to a promising new route for the research.