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The Data Science Workshop

You're reading from   The Data Science Workshop A New, Interactive Approach to Learning Data Science

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Product type Paperback
Published in Jan 2020
Publisher
ISBN-13 9781838981266
Length 818 pages
Edition 1st Edition
Languages
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Authors (5):
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Thomas Joseph Thomas Joseph
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Thomas Joseph
Andrew Worsley Andrew Worsley
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Andrew Worsley
Robert Thas John Robert Thas John
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Robert Thas John
Anthony So Anthony So
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Anthony So
Dr. Samuel Asare Dr. Samuel Asare
Author Profile Icon Dr. Samuel Asare
Dr. Samuel Asare
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Toc

Table of Contents (18) Chapters Close

Preface 1. Introduction to Data Science in Python 2. Regression FREE CHAPTER 3. Binary Classification 4. Multiclass Classification with RandomForest 5. Performing Your First Cluster Analysis 6. How to Assess Performance 7. The Generalization of Machine Learning Models 8. Hyperparameter Tuning 9. Interpreting a Machine Learning Model 10. Analyzing a Dataset 11. Data Preparation 12. Feature Engineering 13. Imbalanced Datasets 14. Dimensionality Reduction 15. Ensemble Learning 16. Machine Learning Pipelines 17. Automated Feature Engineering

Pipelines

During your data science journey, you will have realized that there are various processes to go through before you get any final outcomes, including data cleaning, data transformation, modeling, and so on. You will have found that when we perform these activities separately, we have to write individual steps to carry them out. When we have to do these steps for a new dataset, even if it is similar to another one that we have worked on before, we have to repeat the steps again. As you will have noticed, these steps are tedious and repetitive.

Pipeline is a utility from the scikit-learn library that automates many of these tasks. Using this utility, we can stack multiple processes together for use on multiple datasets. This helps us with a lot of the manual steps involved in the data science journey.

Have a look at Figure 16.1; we have used pipeline processes on multiple different datasets. However, thanks to the pipeline processes we are provided with, we can be sure...

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