MIT Press (MA)
Unsupervised Learning (English, Geoffrey Hinton | Terrence Sejnowski)
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Specifications
| Publisher | MIT Press (MA) |
| Language | English |
| ISBN-13 | 9780262581684 |
| ISBN-10 | 026258168X |
| Author | Geoffrey Hinton | Terrence Sejnowski |
Product Description
About the Book
Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsuperv…
ISBN: 9780262581684
Book Insights
What You'll Learn
- ·In-depth exploration of topics covered in Unsupervised Learning
- ·Key concepts explained with clarity and practical examples
- ·Insights valuable for anyone studying or working in MIT Press (MA)
Who Should Read This
Students and professionals interested in MIT Press (MA), as well as general readers looking to expand their knowledge.
Key Highlights
- ·Brand new physical book delivered across India
- ·15-day hassle-free return policy
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Unsupervised Learning is available in English on GlowMirror.
Who is the author of Unsupervised Learning?
Unsupervised Learning is authored by Geoffrey Hinton | Terrence Sejnowski.
Who published Unsupervised Learning?
Unsupervised Learning is published by MIT Press (MA).
How many pages does Unsupervised Learning have?
Page count information for Unsupervised Learning is available in the specifications section of this page.
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At an average reading speed of 250 words per minute, reading Unsupervised Learning takes a few hours to a few days depending on reading pace.
What is Unsupervised Learning about?
About the Book
Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations ...
Is Unsupervised Learning suitable for beginners?
Whether Unsupervised Learning is suitable for beginners depends on your background in MIT Press (MA). Review the product description and specifications above for details on the target audience and difficulty level.
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Unsupervised Learning is from the MIT Press (MA) edition/year. Check the specifications section for full edition details.
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