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Machine Learning with Go Quick Start Guide

You're reading from   Machine Learning with Go Quick Start Guide Hands-on techniques for building supervised and unsupervised machine learning workflows

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781838550356
Length 168 pages
Edition 1st Edition
Languages
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Authors (2):
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Michael Bironneau Michael Bironneau
Author Profile Icon Michael Bironneau
Michael Bironneau
Toby Coleman Toby Coleman
Author Profile Icon Toby Coleman
Toby Coleman
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Toc

When to use ML

At the outset of any new project, you will need to identify whether ML is the correct approach. This depends on three key factors:

  • First of all, it is crucial to understand your business requirements, and whether it can indeed be tackled by ML. Think about what the goals of your project are. For example, do you want to reduce the cost of a process that currently requires significant manual work and cost? Are you trying to create a better experience for your end customer, for example, by adding personalized features that would be too time-consuming to build using traditional code?
  • Next, ask yourself whether you have the data required to make your proposed ML system work. If not, how will you acquire the data you need, and what potential issues will need to be solved? For example, you might need to bring together datasets from different areas within your organization...
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