Prague – 8 July 2019
Machine learning and rules-based systems are widely used to make inferences from data. It has been found that the two approaches have their strengths and weaknesses, however, it is useful to have a grasp of both.
Although not as popular anymore, rules-based systems do still have their place and it is worth understanding the distinction between these methods and where they might be valuable. You can find more details by searching for "rules-based systems vs machine learning".
Rules-based systems in a nutshell
Rules-based systems are a simple kind of artificial intelligence, which use a series of IF-THEN statements that guide a computer to reach a conclusion or recommendation.
Machine learning is an alternative approach which can help to address some of the issues with rules-based methods. Rather than attempt to fully emulate the decision process of an expert or best practice, machine learning methods typically only take the outcomes from the experts.
During the inaugural PICANTE Tech Conference Europe, Aleksander Kijek, Chief Product Officer at Nethone, will explain how moving from rule based systems into machine learning can benefit your company in a panel discussion dedicated to the growing use of Artificial Intelligence by Start-ups and SMEs.
Aleksander Kijek will be joined by Jiří Třečák (CEO at Supernova) and Vojtech Chloupek (Partner at Bird & Bird).
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