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Hands-On Python Deep Learning for the Web
book

Hands-On Python Deep Learning for the Web

by Anubhav Singh, Sayak Paul
May 2020
Intermediate to advanced
404 pages
10h 52m
English
Packt Publishing
Content preview from Hands-On Python Deep Learning for the Web

Avoiding the chances of getting erroneous data in the first place

What is erroneous data? Are we only talking about data with wrong values? The answer is no. Besides data having wrong or missing values, erroneous data can have subtle but grave errors that may lead to poor training of the model or even bias. So, it is important to identify such erroneous data and remove it before training our model. There are five main ways of identifying these errors:

  • Look for missing values.
  • Look for values that seem out of scale or possibility—in other words, outliers.
  • Do not include any features in the dataset that might cause data leakage.
  • Ensure that all categories of evaluation have a similar number of samples in the dataset.
  • Ensure that your design ...
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Publisher Resources

ISBN: 9781789956085