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Data Cleansing Master Class in Python [Video]
Data Cleansing Master Class in Python [Video]

Data Cleansing Master Class in Python: The Complete Guide to Data Cleansing for Machine Learning Engineers [Video]

By Mike West
$49.99
Video Dec 2021 3 hours 33 minutes 1st Edition
Video
$49.99
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Video
$49.99
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Key benefits

  • Learn how to apply real-world data cleansing techniques to your data
  • Learn advanced data cleansing techniques
  • Learn how to prepare data in a way that avoids data leakage, and in turn, incorrect model evaluation

Description

Data preparation may be the most important part of a machine learning project. It is the most time-consuming part, although it is the least discussed topic. Data preparation, sometimes referred to as data preprocessing, is the act of transforming raw data into a form that is appropriate for modeling. Machine learning algorithms require input data to be numbered, and most algorithm implementations maintain this expectation. Therefore, if your data contains data types and values that are not numbers, such as labels, you will need to change the data into numbers. Further, specific machine learning algorithms have expectations regarding the data types, scale, probability distribution, and relationships between input variables, and you may need to change the data to meet these expectations. In this course, you will learn data imputation and advanced data cleansing techniques, how to apply real-world data cleansing techniques to your data, advanced data cleansing techniques. Also, learn how to prepare data in a way that avoids data leakage, and in turn, incorrect model evaluation. By the end of this course, you will perform data preprocessing and master data cleaning skills. The complete code bundle for this course is available at https://github.com/PacktPublishing/Data-Cleansing-Master-Class-in-Python

What you will learn

Prepare data in a way that avoids data leakage Identify and handle problems with messy data Know which feature selection method to choose based on the data types Transform the probability distribution of input variables Identify and remove irrelevant and redundant input variables Project variables into a lower-dimensional space

Product Details

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Publication date : Dec 17, 2021
Length 3 hours 33 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781803239040
Category :
Concepts :

What do you get with a video?

Product feature icon Download this video in MP4 format
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
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Product Details


Publication date : Dec 17, 2021
Length 3 hours 33 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781803239040
Category :
Concepts :

Table of Contents

7 Chapters
1. Introduction Chevron down icon Chevron up icon
2. Foundations Chevron down icon Chevron up icon
3. Data Cleansing Chevron down icon Chevron up icon
4. Feature Selection Chevron down icon Chevron up icon
5. Data Transforms Chevron down icon Chevron up icon
6. Advanced Transforms Chevron down icon Chevron up icon
7. Dimensionality Reduction Chevron down icon Chevron up icon

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