A Study on Machine Learning: Algorithms and Applications

  • Kona Krishna Priya, Kamala Priyadarshini K


Machine Learning was the phenomenal outcomewhen Computer Science and Statistics joined forces. Computer Science focuses on building machines that solve particular problems, and tries to identify if problems are solvable at all. The main approach that Statistics fundamentally employs is data inference, modeling hypothesises and measuring reliability of the conclusions.The defining ideaof Machine Learning is a little different but partially dependent on both nonetheless. Whereas Computer Science concentrate on manually programming computers, MLaddressesthe problem of getting computers to re-program themselves whenever exposed to new data based on some initial learning strategies provided. On the other hand, Statistics focuses on data inference and probability, Machine Learning includes additional concerns about thefeasibility and effectiveness of architectures and algorithms to process those data, compounding several learning tasks into a compact one and performance measures.

 Keywords: accuracy, algorithm, data, Machine Learning, mathematics, statistics, training.