Paper Details

Gathering and maintaining large collections of data is one thing, but extracting useful information fromthese collections is even more challenging. Most industries working with large amounts of data have recognized thevalue of machine learning technology. By gleaning insights from this data – often in real time – organizations are able towork 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 alsopresent a brief review few applications of machine leaning in real time prediction, think of business cases such asproduct recommendation, market forecasting, segmentation of customers, fraud detection or churn prevention. Machinelearning techniques can solve such applications using a set of generic methods that differ from more traditionalstatistical techniques. The emphasis is on real-time and highly scalable predictive analytics, using fully automatic andgeneric methods that simplify some of the typical data scientist tasks.

Firasath Nabi, Sanjay Jamwal, Kumar Padmanbh, “Machine Learning for Data Analysis and its Applications”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 13, pp. -, January 2018.