Paper Review: The Discipline of Machine Learning - Author: Tom M. Mitchell

This is a best paper to start understanding Machine Learning. In this paper author explains about Machine learning, its current progress, future long-term research and real world applications. After reading this paper one can understand the basics of Machine Learning and its application in various areas. Machine Learning is about how systems automatically learns algorithms to improves its performance (P ) at task (T) with its experience of (E).  The learning task might of various types like data mining, data base updating, programming by example etc. The Machine Learning couples the fields of Computer Science and Statistics, computer science focuses on programming whereas statistics helps in getting best inference from the data.

Currently Machine learning being used for Speech recognition, Medical and Biological sciences, Robot control, Bio-surveillance, Image identification and classification etc. While talking about medical data (structured data), Machine Learning can be used to predict outcome of patient with particular treatment. Speech recognition and face recognition technologies are widely used in mobile, computer applications and in social media (Facebook face tagging), this can help greatly in surveillance systems as well. Machine learning is adopted in US Post Office to automatically sort the letters containing hand written address. Machine Learning is being used to learn the models of gene expression to the astronomical data.

Machine Learning methods play key role in computer science, as it makes us think beyond normal programming. There will be a shift in thinking from “how to program computers” to “how they program themselves”, this way it will help in self-diagnose and self-repair. Current challenges in Machine Learning are how to reduce the supervised learning with the help of unlabeled data, can machine get best training data by itself and how can we make system to understand the relationship between different algorithms. Another challenge would be of maintaining data privacy; while we can train a medical diagnosis system on data from all hospitals in the world it should also maintain the privacy of each subject. On the other hand there are researches on machine learning which are of long run like how would we build a never ending learner.  Theories and algorithms using Machine Learning are used to understand the human learning.

Author concludes the paper discussing on ethical issues which may arise from the Machine learning technology. The Machine Learning will be useful in clinical research and medical fields but question arises how would we protect data privacy of an individual in such studies? Similarly one should have enough understanding to maintain privacy of data collected from law enforcement or for marketing purpose.