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Deep learning from scratch : building with Python from first principles / Seth Weidman

By:

Weidman, Seth

Material type: Text

TextPublication details: India O'Reilly / SPD 2019Description: 235 pISBN:

9789352139026

Subject(s):

DDC classification:

006.32 WEI-S

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)	006.32 WEI-S (Browse shelf(Opens below))	Available		40374

Total holds: 0

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Previous	006.32 TAN-H Neural networks : computational models and applications /	006.32 TAN-H Neural networks : computational models and applications /	006.32 WAR-K Strengthening deep neural networks : making AI less susceptible to adversarial trickery /	006.32 WEI-S Deep learning from scratch : building with Python from first principles /	006.33 AGA-D Statistical methods for recommender systems /	006.33 DAR-K Essence of expert systems /	006.33 GOM-A Ontological engineering with examples from the areas of knowledge management, e-Commerce and the semantic web /	Next

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way.

Author Seth Weidman shows you how neural networks work using a first principles approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning projects.

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