A Study on Machine Learning Algorithms and its Applications
Mrs S.Subhashini , Mrs.Y.sharmila Begam, Dr.P.Umamaheswari
Research Scholar , Anna university Regional campus, Madurai,
Research Scholar , Anna university Regional campus, Madurai,
Assistant Professor, Dept of computer science, Anna university Regional campus, Madurai
E-mail :subhacsmsn@gmail.com,, sharmila.yusuf@gmail.com ,dharshukiran@gmail.com
Abstract
Machine learning is one of the rapidly developing fields of technology . It is growing very rapidly day by day . Applications of machine learning are vast in our daily life. Recently machine learning techniques are used in Google Maps, Google assistant, Alexa, Cortana, Siri etc. Machine learning's face detection and recognition algorithm are used in facebook for automatic friend tagging suggestion. ML algorithms for speech recognition is used in search by voice in google maps which shows the correct shortest route and predicts the traffic conditions. ML algorithms are also used for product recommendation to the user in Amazon, Netflix . Tesla, the car manufacturing company uses ML algorithms in manufacturing self driving cars .Machine learning algorithms such as multi-Layer Perceptron, Decision tree, and Naïve Bayes classifier are used for email spam filtering and malware detection. Voice instructions such as Play music, call someone, Open an email, Scheduling an appointment, etc. are given in virtual assistants using machine learning algorithms . Machine learning makes online transaction safe and secure by detecting fraud transaction, fake accounts, fake ids, and steal money in the middle of a transaction. Feed Forward Neural network algorithms checks whether it is a genuine transaction or a fraud transaction. Machine learning's long short term memory neural network is used for the prediction of stock market trends. Machine learning is used for disease diagnoses and Google's GNMT (Google Neural Machine Translation) which converts the text into our known languages. In this article, ML applications and various steps involved in ML life cycle are discussed . This article presents a study about various types of ML algorithms , ML in data processing, ML in data cleaning and challenges of ML ..
Keywords: Machine learning , supervised learning, unsupervised learning , Data cleaning, Model training.
