Discover deep learning and computer vision with SAS!
Deep Learning for Computer Vision with SAS®: An Introduction introduces the pivotal components of deep learning. Readers will gain an in-depth understanding of how to build deep feedforward and convolutional neural networks, as well as variants of denoising autoencoders. Transfer learning is covered to help readers learn about this emerging field. Containing a mix of theory and application, this book will also briefly cover methods for customizing deep learning models to solve novel business problems or answer research questions. SAS programs and data are included to reinforce key concepts and allow readers to follow along with included demonstrations.
Readers will learn how to:
Define and understand deep learning
Build models using deep learning techniques and SAS Viya
Apply models to score (inference) new data
Modify data for better analysis results
Search the hyperparameter space of a deep learning model
Leverage transfer learning using supervised and unsupervised methods
Discover deep learning and computer vision with SAS!
Deep Learning for Computer Vision with SAS®: An Introduction introduces the pivotal components of deep learning. Readers will gain an in-depth understanding of how to build deep feedforward and convolutional neural networks, as well as variants of denoising autoencoders. Transfer learning is covered to help readers learn about this emerging field. Containing a mix of theory and application, this book will also briefly cover methods for customizing deep learning models to solve novel business problems or answer research questions. SAS programs and data are included to reinforce key concepts and allow readers to follow along with included demonstrations.
Readers will learn how to:
Define and understand deep learning
Build models using deep learning techniques and SAS Viya
Apply models to score (inference) new data
Modify data for better analysis results
Search the hyperparameter space of a deep learning model
Leverage transfer learning using supervised and unsupervised methods
Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks Key Features Train different kinds of deep learning model from scratch to solve specific problems...
Computer Vision (CV) have seen a massive rise in popularity in the remote sensing field over the last few years. This success is mostly due to the effectiveness of deep learning (DL) algorithms...
3D deep learning is a rapidly evolving field that has the potential to transform various industries. This book provides a comprehensive overview of the current state-of-the-art in 3D deep learning,...
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