WEBVTT
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Language: en
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Hi everyone and welcome to our Big Data Analytics
collection of courses. My name is Kerrie Mengersen.
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You might be thinking, what is the relationship
between mathematics and Big Data?
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Well, let me paint a picture for you:
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imagine you’re a marketing analyst for a big company about to launch a brand new product.
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Your job is to use people’s social media usage to determine the target market for your product and sell it.
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These days the increase is social media is explosive -
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every day there are 4.5 billion likes on Facebook, over 500 million tweets on Twitter
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and more than 75 million people using Instagram.
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With this much data, your job in making any sense of this information becomes extremely difficult.
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Enter mathematics!
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With the right mathematical techniques and tools, your job quickly becomes much easier.
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We can use mathematics to not
only effectively store and manage data,
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but to efficiently analyse it and extract information
that is not immediately obvious.
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In this course we present a numerical linear algebra framework for data analytics.
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This includes a wide range of mathematical methods for big data analytics
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such as the singular value decomposition, tensor products, matricization, graph Laplacian and clustering.
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We show you how to apply these techniques to store, manage and analyse Big Data.
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Here at ACEMS we use a multi-lensed approach to Big Data analytics
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and this is reflected in the case studies
we’ll share with you.
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Mathematics is everywhere, and can help you solve lots of different problems.
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We’re very excited about this course,
and we hope you are too.