Build state-of-the-art one-shot learning models in computer vision and NLP with the power of Keras About This Book * Learn how one-shot learning speeds up the deep learning process * Leverage the power of Python and Keras to build state-of-the-art one-shot learning models * Covers one-shot learning architectures, such as Siamese Networks and Memory Augmented Networks Who This Book Is For AI researchers, as well as machine learning and deep learning experts who wish to apply one-shot learning to reduce the overall training time of their models, will find this book to be a very good introductory source of learning. Knowledge of basic machine learning and deep learning concepts, their underlying mathematics, as well as exposure to Python programming is required for this book. What You Will Learn * Understand the fundamental concept of one/few-shot learning * Work with different deep learning architectures for one-shot learning * Know when to use one-shot and when to use transfer learning * Explore the Bayesian network approach to one-shot learning * Implement Siamese Networks and Memory Augmented Networks in Keras * Explore various Computer Vision and NLP-based one-shot learning architectures In Detail One-shot learning has been an active field of research for many scientists who are trying to find a cognitive machine as close to humans in terms of learning. As there are various theories about how humans do one-shot learning, we have a lot of different methods to achieve it, ranging from non-parametric models, Deep Learning Architectures, and Probabilistic Models. This book will focus on designing and learning about models which can learn information about an object from one, or only a few, training examples. The book will begin by giving you a brief overview of deep learning and one-shot learning to get you started. Then you will learn different methods to achieve it, ranging from Non-parametric models, Deep Learning Architectures, and Probabilistic Models with majorly focus on teaching possible methods of implementing One-shot learning and their implementations. Once you are well versed with the core principles, you will explore some of the practical real-world examples and implementations of one-shot learning using scikit-learn and Keras 2.x in Computer Vision and Natural Language Processing. By the end of the book, you will be well versed with understanding one/few shots learning methods and will be able to speed up your deep learning processes with one-shot learning.

Book Information
ISBN 9781838825461
Author Shruti Jadon
Format Paperback
Page Count 207
Imprint Packt Publishing Limited
Publisher Packt Publishing Limited