ABSTRACT
In today’s world, it is obvious that the use of digital data, i.e., big data, is rapidly expanding. Generation of useful information from proliferated data is an engrossing process that is referred to as “training of the data”. Nowadays, trained data sets have a vital role in finding knowledge through machine learning (ML). This paper presents new ideas in ML or deep learning techniques for machines in the field of training data for high-performance computing. It represents the survey of various ML techniques or methods applied prior to training data sets for knowledge extraction in big data analytics to enhance high-performance computing like cloud computing or grid computing. This paper could be seen as the origin and basis of research and has a key value in the field of ML.
