Image Data
128 🏗️ Noise Reduction

Feature Engineering A-Z

Preface
Introduction
Numeric Features
Categorical Features
Datetime Features
Missing Data
Text Features
Circular Features
Too Many Variables
Correlated Data
- 79 Correlated Overview
- 80 High Correlation Filter
Outliers
Imbalanced Data
Miscellaneous
Spatial
Time-Series Data
Image Data
Ralational Data
Video Data
- 138 Video Overview
- 139 🏗️ Temporary
Sound Data
- 140 Sound Overview
- 141 🏗️ Temporary
142 🏗️ Order of transformations
143 🏗️ What should you do if you have sparse data?
144 🏗️ How Different Models Deal With Input
145 🏗️ Summary
References

Table of contents

128.1 Noise Reduction
128.2 Pros and Cons
- 128.2.1 Pros
- 128.2.2 Cons
128.3 R Examples
128.4 Python Examples

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Image Data
128 🏗️ Noise Reduction

128 🏗️ Noise Reduction

128.1 Noise Reduction

WIP

128.2 Pros and Cons

128.2.1 Pros

128.2.2 Cons

128.3 R Examples

128.4 Python Examples

127 🏗️ Color Modifications

129 🏗️ Value Normalization' class='pagination-link' href='/image-normalization'> 129 🏗️ Value Normalization

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