Machine Learning for Data Analysis and its Applications

Abstract

Gathering and maintaining large collections of data is one thing, but extracting useful information from
these collections is even more challenging. Most industries working with large amounts of data have recognized the
value of machine learning technology. By gleaning insights from this data – often in real time – organizations are able to
work more efficiently or gain an advantage over competitors. The interest in predicting future outcomes using your data?
Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal.
This paper focusses on the available machine learning approach for real-time processing of data. The paper will also
present a brief review few applications of machine leaning in real time prediction, think of business cases such as
product recommendation, market forecasting, segmentation of customers, fraud detection or churn prevention. Machine
learning techniques can solve such applications using a set of generic methods that differ from more traditional
statistical techniques. The emphasis is on real-time and highly scalable predictive analytics, using fully automatic and
generic methods that simplify some of the typical data scientist tasks.