While scrolling through my Linkedin page on a sultry Saturday afternoon, I read through a post where some folks argued about the limitations of Machine Learning and why they think it is overhyped. Their underlying argument was that ML is only useful for predictions and really not worth the stress of having to go through all the rigour just to build a model. This came to me, not as a surprise because there has been this silent consensus amongst data science enthusiasts who doubt the value of ML.

To safeguard against this notion and to contribute the to rising call…

Introduction

As estimates suggest, Non-Technical Loss(NTL) in any sub-Saharan power distribution company may range up to 40% of the total energy received from the grid. Industrial NTL detection systems are still largely based on expert knowledge when deciding whether to carry out costly on-site inspections of customers.

With millions of prepaid meters soon to be deployed to most households through the National Mass Metering Programme, power distribution companies would have to find novel ways to deal with the challenges of meter bypass and energy theft as a whole. …

Tams George

I transform raw customer data into actionable insights for better decision making.

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