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White Paper

Implementing AWS Machine Learning in your organisation in 6 steps

Global Knowledge
  • Date: 01 January, 0001

Abstract

From smart voice assistants to self-driving cars, and from smart product configurators to
predictive models that have the potential to minimise the damage caused by climate change,
machine learning is reshaping the ways in which we interact with machines, the world and our
fellow human beings. Machine learning is quickly becoming one of the hottest technologies on
the market, mainly because it has the potential to greatly improve services, applications and
devices.

Data warehouses and lakes are becoming so big and vast that humans are unable to manually
process all of this information. This is where machine learning comes in. The technology allows
companies and individuals to process and analyse huge chunks of information in a largely
automated manner.

In this whitepaper, we are going to take a look at a phenomenon called machine learning. We will
also show you how to sustainably implement the power of machine learning in your organisation
using the AWS platform, along with the accompanying AWS services. So be sure to read on if
you want to harness the full power of machine learning to grow your business and improve your
services.

Sample

Challenge 1: Accessibility of data
Machine learning only produces valuable output if you feed it with raw data. And properly training machine learning algorithms requires huge amounts of data. Many organisations don’t gather enough data or fail to make their data accessible, so their information becomes siloed and is not stored in the right places.

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