Book Image

Synthetic Data for Machine Learning

By : Abdulrahman Kerim
Book Image

Synthetic Data for Machine Learning

By: Abdulrahman Kerim

Overview of this book

The machine learning (ML) revolution has made our world unimaginable without its products and services. However, training ML models requires vast datasets, which entails a process plagued by high costs, errors, and privacy concerns associated with collecting and annotating real data. Synthetic data emerges as a promising solution to all these challenges. This book is designed to bridge theory and practice of using synthetic data, offering invaluable support for your ML journey. Synthetic Data for Machine Learning empowers you to tackle real data issues, enhance your ML models' performance, and gain a deep understanding of synthetic data generation. You’ll explore the strengths and weaknesses of various approaches, gaining practical knowledge with hands-on examples of modern methods, including Generative Adversarial Networks (GANs) and diffusion models. Additionally, you’ll uncover the secrets and best practices to harness the full potential of synthetic data. By the end of this book, you’ll have mastered synthetic data and positioned yourself as a market leader, ready for more advanced, cost-effective, and higher-quality data sources, setting you ahead of your peers in the next generation of ML.
Table of Contents (25 chapters)
1
Part 1:Real Data Issues, Limitations, and Challenges
5
Part 2:An Overview of Synthetic Data for Machine Learning
8
Part 3:Synthetic Data Generation Approaches
13
Part 4:Case Studies and Best Practices
18
Part 5:Current Challenges and Future Perspectives

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter (now, X) handles. Here is an example: “Please note that the seed parameter will help us to get diverse images in this example.”

A block of code is set as follows:

//Example of Non-learning AI (My AI Doctor!)
Patient.age //get the patient's age
Patient. temperature //get the patient's temperature
Patient.night_sweats //get if the patient has night sweats
Paitent.Cough //get if the patient coughs

Tips or important notes

Appear like this.