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Normalize Data to Make It Appropriate for an Analysis with Pandas

Data normalisation transforms our data to make it more tractable for downstream applications. This course will teach you the skills of data normalization in Pandas needed to make any dataset usable for machine learning.

Intermediate
47m
(11)

Created by Axel Sirota

Last Updated May 16, 2023

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  • Course

Normalize Data to Make It Appropriate for an Analysis with Pandas

Data normalisation transforms our data to make it more tractable for downstream applications. This course will teach you the skills of data normalization in Pandas needed to make any dataset usable for machine learning.

Intermediate
47m
(11)

Created by Axel Sirota

Last Updated May 16, 2023

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  • Data
What you'll learn

Regardless of your line of work, data is everywhere. Nowadays we generate more data per second than ever before; however this data is usually raw, dirty and frequently unusable.

In this course, Normalize Data to Make It Appropriate for an Analysis with Pandas, you’ll gain the ability to normalize your data however you need - both to create amazing visualizations as well as feed it into your AI models.

First, you’ll explore what normalization and scaling really are.

Next, you’ll discover some simple techniques like simple scaling or min-max scaling.

Finally, you’ll learn how to perform Z-score scaling which presents your data into a normal distribution.

When you’re finished with this course, you’ll have the skills and knowledge of data normalization needed to make any type of dataset usable.

Normalize Data to Make It Appropriate for an Analysis with Pandas
Intermediate
47m
(11)
Table of contents

About the author
Axel Sirota - Pluralsight course - Normalize Data to Make It Appropriate for an Analysis with Pandas
Axel Sirota
36 courses 3.6 author rating 1141 ratings

Axel Sirota has a Masters degree in Mathematics with a deep interest in Deep Learning and Machine Learning Operations. After researching in Probability, Statistics and Machine Learning optimization, he is currently working at JAMPP as a Machine Learning Research Engineer leveraging customer data for making accurate predictions at Real Time Bidding.

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