Benyamin Ghojogh – författare
Visar alla böcker från författaren Benyamin Ghojogh. Handla med fri frakt och snabb leverans.
6 produkter
Elements of Dimensionality Reduction and Manifold Learning
Av Benyamin Ghojogh, Mark Crowley m. fl.
Inbunden, 2023
1129 kr
Lägg i varukorg
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and …
Elements of Dimensionality Reduction and Manifold Learning
Av Ali Ghodsi, Fakhri Karray m. fl.
E-bok, 2023
985 kr
Lägg i varukorg
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and …
Elements of Dimensionality Reduction and Manifold Learning
Av Benyamin Ghojogh, Mark Crowley
2023
686 kr
Lägg i varukorg
Elements of Dimensionality Reduction and Manifold Learning
Av Benyamin Ghojogh, Mark Crowley m. fl.
Häftad, 2024
792 kr
Lägg i varukorg
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and …
Elements of Deep Learning
Av Benyamin Ghojogh, Ali Ghodsi
Inbunden, 2026
1241 kr
Lägg i varukorg
This textbook offers a comprehensive introduction to deep learning and neural networks, integrating core foundations with the latest advances. It begins with essential machine learning concepts and classic neural network architectures before progressing through convolutional models, …
Elements of Deep Learning
Av Ali Ghodsi, Benyamin Ghojogh
E-bok, 2026
1670 kr
Lägg i varukorg
This textbook offers a comprehensive introduction to deep learning and neural networks, integrating core foundations with the latest advances. It begins with essential machine learning concepts and classic neural network architectures before progressing through convolutional models, …