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Deep leaning neural networks : design and case studies / Daniel Graupe

By:

Graupe, Daniel

Material type: Text

TextPublication details: New Jersey World Scientific 2020Description: 263pISBN:

9780000988546

Subject(s):

DDC classification:

006.31 GRA-D

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Collection	Shelving location	Call number	Status	Date due	Barcode	Item holds
Books	BITS Pilani Hyderabad	003-007	General Stack (For lending)	006.31 GRA-D (Browse shelf(Opens below))	Available		44955

Total holds: 0

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Previous	006.31 GIA-N How algorithms create and prevent fake news : exploring the impacts of social media, deepfakes, GPt-3, and more /	006.31 GIF-N Practical MLOps : operatonalizing machine learning models /	006.31 GOU-J Probabilistic machine learning for civil engineers /	006.31 GRA-D Deep leaning neural networks : design and case studies /	006.31 GRA-T Kubeflow for machine learning : from lab to production /	006.31 HEB-P Machine learning for designers /	006.31 HEL-H Machine learning for oracle database professionals : deploying model-driven applications and automation pipelines /	Next

Deep learning neural networks are the fastest-growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems based on a well-defined computational architecture. It has been successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance. This comprehensive textbook is the first in the newly emerging field. Numerous case studies are succinctly demonstrated in the text. It is intended for use as a one-semester graduate Level University text and as a textbook for research and development establishments in the industry, medicine and financial research.

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