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Machine Learning for decision making

by Changepond  Posted on October 9, 2018

Find out how Changepond helped UK’s largest Telecom utility service provider in reducing operational costs and improving operational efficiency using Machine Learning.



The increasing availability of data is changing decision making process of organizations across the globe. Machine learning (ML) approaches have been assisting the decision making process facilitated by the growing capability of cloud native tools and rising know how around the commercial usage of statistical methods and algorithms using analysis friendly programming languages. According to studies 61% of organizations has identified ML as their company’s most significant initiative for 2018, of the respondents 58% indicated they ran models in production. Deloitte Global predicts ML pilots and implementations to double by 2020.

While ML has typically linked with industries such as banking, e-commerce, transportation etc., there are many uses for ML in utilities industry as well. Recent trends suggest that the use of ML in utilities sector will accelerate. Some of the use cases where ML has advantage over traditional analysis techniques include customer segmentation, pricing forecasting, anomaly detection and predictive maintenance. Utilities industry is already using ML algorithms particularly in the field of asset monitoring, predictive maintenance and predictive monitoring.

In this webinar we will focus on some of the basic principles of ML and how Changepond helped one of our customers in Telecom utility service provider to reduce operational costs and improve operational efficiency.

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Machine learning for decision making

Find out how Changepond helped UK’s largest Telecom utility service provider in reducing operational costs and improving operational efficiency using Machine Learning.



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