Lifelong Machine Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning)

Chen, Zhiyuan Zhiyuan Chen, Bing Liu,

ISBN 10: 1627055010 / ISBN 13: 9781627055017

Published by Morgan and Claypool Life Sciences, 2016

About this Item

Lifelong Machine Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .

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Bibliographic Details

• Title: Lifelong Machine Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning)
• Publisher: Morgan and Claypool Life Sciences
• Publication Date: 2016
• Language: English
• ISBN 10: 1627055010
• ISBN 13: 9781627055017
• Binding: paperback
• Condition: Very Good

About this title

Synopsis

Lifelong Machine Learning (or Lifelong Learning) is an advanced machine learning paradigm that learns continuously, accumulates the knowledge learned in previous tasks, and uses it to help future learning. In the process, the learner becomes more and more knowledgeable and effective at learning. This learning ability is one of the hallmarks of human intelligence. However, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model. It makes no attempt to retain the learned knowledge and use it in future learning. Although this isolated learning paradigm has been very successful, it requires a large number of training examples, and is only suitable for well-defined and narrow tasks. In comparison, we humans can learn effectively with a few examples because we have accumulated so much knowledge in the past which enables us to learn with little data or effort. Lifelong learning aims to achieve this capability. As statistical machine learning matures, it is time to make a major effort to break the isolated learning tradition and to study lifelong learning to bring machine learning to new heights. Applications such as intelligent assistants, chatbots, and physical robots that interact with humans and systems in real-life environments are also calling for such lifelong learning capabilities. Without the ability to accumulate the learned knowledge and use it to learn more knowledge incrementally, a system will probably never be truly intelligent. This book serves as an introductory text and survey to lifelong learning.

About the Author

Google, Inc.