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You're reading from  Hands-On Data Preprocessing in Python

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Published inJan 2022
PublisherPackt
ISBN-139781801072137
Edition1st Edition
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Roy Jafari
Roy Jafari
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Roy Jafari

Roy Jafari, Ph.D. is an assistant professor of business analytics at the University of Redlands. Roy has taught and developed college-level courses that cover data cleaning, decision making, data science, machine learning, and optimization. Roy's style of teaching is hands-on and he believes the best way to learn is to learn by doing. He uses active learning teaching philosophy and readers will get to experience active learning in this book. Roy believes that successful data preprocessing only happens when you are equipped with the most efficient tools, have an appropriate understanding of data analytic goals, are aware of data preprocessing steps, and can compare a variety of methods. This belief has shaped the structure of this book.
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Exercises

  1. In your own words, describe the similarities and differences between data reduction and data redundancy from the following angles: the literal meanings of the terms, their objectives, and their procedures.
  2. If you decide to include or exclude independent attributes based on the correlation coefficient value of each independent attribute with the dependent attribute in a prediction task, what would you call this type of preprocessing? Data redundancy or data reduction?
  3. In this example, we will be using new_train.csv from https://www.kaggle.com/rashmiranu/banking-dataset-classification. Each row of the data contains customer information, along with campaign efforts regarding each customer, to get them to subscribe for a long-term deposit at the bank. In this example, we would like to tune a decision tree that can show us the trends that lead to successful subscription campaigning. As the only tuning process we know about will be computationally very expensive, we...
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Hands-On Data Preprocessing in Python
Published in: Jan 2022Publisher: PacktISBN-13: 9781801072137

Author (1)

author image
Roy Jafari

Roy Jafari, Ph.D. is an assistant professor of business analytics at the University of Redlands. Roy has taught and developed college-level courses that cover data cleaning, decision making, data science, machine learning, and optimization. Roy's style of teaching is hands-on and he believes the best way to learn is to learn by doing. He uses active learning teaching philosophy and readers will get to experience active learning in this book. Roy believes that successful data preprocessing only happens when you are equipped with the most efficient tools, have an appropriate understanding of data analytic goals, are aware of data preprocessing steps, and can compare a variety of methods. This belief has shaped the structure of this book.
Read more about Roy Jafari