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What problems can machine learning solve for you?

Kirsten Doyle
By Kirsten Doyle, ITWeb contributor.
Johannesburg, 30 Jul 2018
Dr Natasha Govender, lead data scientist at DotModus.
Dr Natasha Govender, lead data scientist at DotModus.

With all the hype around big data, artificial intelligence (AI), and machine learning, what are the real-world business applications and benefits of machine learning?

Meeting of Minds: ITWeb Artificial Intelligence 2018

Register now to attend the Meeting of Minds: ITWeb Artificial Intelligence 2018 at The Forum, Bryanston on 1 and 2 August 2018. Dr Natasha Govender will join other industry leaders in discussing their experience of the best practices for artificial intelligence, machine learning, IoT and robotics. For the most up-to-date agenda, click here.

While most businesses have heard of machine learning, many have not fully grasped what it actually is, the areas in which it can be applied, the business problems it can help to solve, or the true value it can add to their organisation.

During the Meeting of Minds: ITWeb Artificial Intelligence 2018, to be held on 1 and 2 August at The Forum in Bryanston, Dr Natasha Govender, lead data scientist at DotModus, will discuss 'Using machine learning to gain business insights'.

"Any company that has data and wants to find a way to make sense of it can benefit from machine learning," she says.

Machine learning algorithms learn from the data iteratively and enable machines to find different types of hidden insights without being expressly told to do so. However, Govender says machine learning is not without limitations.

"Machine learning cannot solve all problems. While it can provide insights into data for unsupervised learning algorithms, for supervised learning algorithms, it can only learn and make decisions based on the data that is provided."

Dr Govender's talk will cover what machine learning really is. She will provide a high-level explanation of the different types of machine learning techniques, how it can be applied to data, and how this, in turn, can be used to produce quantifiable outcomes for companies in various sectors.

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