April 2023
Intermediate to advanced
394 pages
8h 45m
English
Data augmentation is essential for developing a successful deep learning (DL) project. However, data scientists and developers often overlook this crucial step. It is no secret that you will spend the majority of your project time gathering, cleaning, and augmenting the dataset in a real-world DL project. Thus, learning how to expand the dataset without purchasing new data is essential. This book covers standard and advanced techniques for extending image, text, audio, and tabular datasets. Furthermore, you will learn about data biases and learn how to code on Jupyter Python Notebooks.
Chapter 1 will introduce various data augmentation concepts, set up the coding environment, and create the foundation class. Later ...