Advances in machine learning algorithms and an explosion in software tools have ushered in a transformative period for business, science and medicine. Machine learning is now one of the hottest topics in the World. However, there is far more to successful implementation of Machine Learning than just creating great models. Algorithms are just the tip of the iceberg when it comes to creating business and customer value from data.
There are barriers and complications to successful real-world implementation of machine learning projects. This presentation will outline practical solutions to overcoming them including: selling the benefits to the business; collaborating with data engineers to deliver supporting data infrastructure; learning from, and working with developers to put models into production; building testing into the process and future-proofing ongoing maintenance of the solution.
Resource invested in these areas ultimately generates higher return than time spent building the perfect machine learning model.
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Machine Learning - What They Don’t Teach You At Coursera - Harvinder Atwal
Harvinder Atwal is Head of Data Strategy and Advanced Analytics. He leads a team of analysts to deliver data-driven customer insight, marketing optimisation and predictive analytics for Moneysupermarket from one of the largest customer databases in the UK with records for 23 million unique individuals.