CONTINUUM Books
Parameter-Efficient Learning
A practical introduction
Textbook · multiple authors
Parameter-Efficient Learning
A practical introduction
Published 18 June 2026 · 248 pages · English
ISBN 978-0-00-100002-9 · DOI 10.xxxx/ctm.bk.2026.0002
Sample book. Title, authors and content are fictional demonstration material.
About this book
An introductory textbook on adapting large pretrained models cheaply. Starting from the linear algebra of low-rank updates, it covers adapters, prompt tuning, quantisation-aware training and deployment, with exercises and solutions for each chapter.
Keywords fine-tuning · adapters · LoRA · teaching
Read or download
parameter-efficient-learning-introduction.pdf
parameter-efficient-learning-introduction.epub
Contents
- 1The cost of fine-tuningpp. 1–18PDF
- 2Low-rank structurepp. 19–46PDF
- 3Adapters and prompt methodspp. 47–86PDF
- 4Quantisation and QLoRA-style trainingpp. 87–126PDF
- 5Choosing hyper-parameterspp. 127–158PDF
- 6Scaling behaviourpp. 159–190PDF
- 7Deployment on small devicespp. 191–226PDF
- 8Exercises and solutionspp. 227–248PDF
About the authors
- Priya Venkataraman · Meridian University, India
Studies parameter-efficient adaptation and the scaling behaviour of fine-tuning methods.
- Daniel Okafor · Northgate Institute of Technology, Nigeria
Works on distillation, quantisation and compression of neural networks.
How to cite
Venkataraman, P. & Okafor, D. (2026). Parameter-Efficient Learning: A practical introduction (1st edition). CONTINUUM Books. doi:10.xxxx/ctm.bk.2026.0002