A practical guide to machine learning
14 May 2018
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While machine learning adoption has been recently accelerated by the explosion of big data and cloud computing, choosing an appropriate machine learning technique can still be a daunting task, particularly when there are so many options available. Machine learning is here to help, but how does it work? Find out more in Ocado Technology’s latest blog post.
Almost every industry nowadays claims to be using the power of artificial intelligence (AI), or more specifically, machine learning (ML) to solve a range of complex real-world challenges. Many businesses have found that, when compared to traditional approaches, machine learning provides better ways to predict real-world outcomes and analyse large data sets with incredible accuracy and speed, uncovering insights that would otherwise remain hidden.
In addition, machine learning has the ability to capture the desired behaviour of experts (humans or other machines) and replay the learned behaviour through the software at much larger scale, usually to provide support for non-experts.
When designing a machine learning system, data scientists have several options available, depending on whether the computer is given any feedback during the learning phase.
Read about these options in detail in Ocado Technology’s blog post, ‘A practical guide to machine learning’.
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