Elements of Deep Learning

Author:   Benyamin Ghojogh ,  Ali Ghodsi
Publisher:   Springer Nature Switzerland AG
ISBN:  

9783032107374


Pages:   461
Publication Date:   21 February 2026
Format:   Hardback
Availability:   Not yet available   Availability explained
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Elements of Deep Learning


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Author:   Benyamin Ghojogh ,  Ali Ghodsi
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9783032107374


ISBN 10:   3032107377
Pages:   461
Publication Date:   21 February 2026
Audience:   General/trade ,  General
Format:   Hardback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

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Benyamin Ghojogh received the B.Sc. degree in electrical engineering from the Amirkabir University of Technology, Tehran, Iran, in 2015, the M.Sc. degree in electrical engineering from the Sharif University of Technology, Tehran, Iran, in 2017, and Ph.D. in electrical and computer engineering (in the area of pattern analysis and machine intelligence) from the University of Waterloo, Waterloo, ON, Canada, in 2021. He was a postdoctoral fellow, focusing on machine learning, at the University of Waterloo, in 2021. He is the co-author of Elements of Dimensionality Reduction and Manifold Learning, published by Springer. His research interests include machine learning, deep learning, dimensionality reduction, data science, and computer vision. Ali Ghodsi is a Professor of Statistics and Computer Science at the University of Waterloo, Director of the Data Science Lab, and a Faculty Affiliate at the Vector Institute for Artificial Intelligence. His research focuses on the theoretical foundations and algorithmic development of machine learning and artificial intelligence, with applications in natural language processing, bioinformatics, and computer vision. He is the co-author of Elements of Dimensionality Reduction and Manifold Learning (Springer). His widely viewed online lectures — including a popular deep learning course — make advanced AI topics accessible to a global audience.

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