Machine Learning in Practice: Avoid the Hype and Make it Work for You

Machine Learning is an academic study of algorithms that find interesting patterns in data. However, it is also the foundation of data science and advanced analytics, perhaps best know as the essential technology of data mining and predictive analysis. If you are interested in business intelligence or any form of modern analytics, machine learning has much to offer. When used well, which means when tested and valid machine learning models are deployed to production, it is capable of increasing customer satisfaction, cross-selling products, forecasting future numbers, such as sales or capacity needs, predicting churn and website clicks, or even helping you analyse log data. However, you don’t even need to deploy your models to benefit from the knowledge and insights that they provide—many models can be beautifully visualised to help you see the otherwise hidden truths that your data has to tell. Come listen to Rafal, a veteran of this area, with over a decade of real-world experience, and find out how machine learning can help you deliver better analytics and solutions. Rafal will also point out the connections between ML and Artificial Intelligence, and he will give you a few important tips for avoiding common mistakes, and some of the hype that surrounds this still-complex and rapidly growing field of information technology.

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