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.
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.
Author Name: Axel Sirota
Author Description:
Axel Sirota is a Microsoft Certified Trainer with a deep interest in Deep Learning and Machine Learning Operations. He has a Masters degree in Mathematics and after researching in Probability, Statistics and Machine Learning optimisation, he works as an AI and Cloud Consultant as well as being an Author and Instructor at Pluralsight, Develop Intelligence, and O’Reilly Media.
Table of Contents
- Course Overview
2mins - Why Normalize?
7mins - Some Simple Normalization Techniques
24mins - Gaussian Normalization
14mins
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