This is the code repository for Synthetic Data for Machine Learning, published by Packt.
Revolutionize your approach to machine learning with this comprehensive conceptual guide
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 covers the following exciting features:
- Understand real data problems, limitations, drawbacks, and pitfalls
- Harness the potential of synthetic data for data-hungry ML models
- Discover state-of-the-art synthetic data generation approaches and solutions
- Uncover synthetic data potential by working on diverse case studies
- Understand synthetic data challenges and emerging research topics
- Apply synthetic data to your ML projects successfully
If you feel this book is for you, get your copy today!
All of the code is organized into folders.
The code will look like the following:
//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
Following is what you need for this book: If you are a machine learning (ML) practitioner or researcher who wants to overcome data problems, this book is for you. Basic knowledge of ML and Python programming is required. The book is one of the pioneer works on the subject, providing leading-edge support for ML engineers, researchers, companies, and decision makers.
You will need a version of PyCharm installed on your computer – the latest version, if possible. All code examples have been tested using Python 3.8 and PyCharm 2023.1 (Professional Edition) on Ubuntu 20.04.2 LTS. However, they should work with future version releases, too.
System requirements are mentioned in the following table:
| Software/Hardware | Operating System requirements |
|---|---|
| Python 3.8+ | Windows, Mac OS X, and Linux (Any) |
| PyCharm 2023.1 | Windows, Mac OS X, and Linux (Any) |
Abdulrahman Kerim is a full-time lecturer at the University for the Creative Arts (UCA) and an active researcher at the School of Computing and Communications at Lancaster University, UK. Kerim got his MSc in computer engineering, which focused on developing a simulator for computer vision problems. In 2020, Kerim started his PhD to investigate synthetic data advantages and potentials. His research on developing novel synthetic-aware computer vision models has been recognized internationally. He has published many papers on the usability of synthetic data at top-tier conferences and in journals such as BMVC and IMAVIS. He currently works with researchers from Google and Microsoft to overcome real-data issues, specifically for video stabilization and semantic segmentation tasks.