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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
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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

Understanding the Business Context

The best way to work using a concept is with an example you can relate to. To understand the business context, let's, for instance, consider the following example.

The marketing head of the bank where you are a data scientist approaches you with a problem they would like to be addressed. The marketing team recently completed a marketing campaign where they have collated a lot of information on existing customers. They require your help to identify which of these customers are likely to buy a term deposit plan. Based on your assessment of the customer base, the marketing team will chalk out strategies for target marketing. The marketing team has provided access to historical data of past campaigns and their outcomes—that is, whether the targeted customers really bought the term deposits or not. Equipped with the historical data, you have set out on the task to identify the customers with the highest propensity (an inclination) to buy...

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