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Deep Learning From Scratch: Building with Python from First Principles

By: Publication details: Mumbai : Shroff Publishers & Distributors, 2019Description: 235ISBN:
  • 9789352139026
Subject(s): DDC classification:
  • 006.31 WEI
Summary: 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
List(s) this item appears in: New Arrivals for the Month of August - 2023 | New Arrivals for the Month of September - 2023
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Book Book Alliance College of Engineering and Design CSE & IT 006.31 WEI (Browse shelf(Opens below)) Available E12310
Book Book Alliance College of Engineering and Design CSE & IT 006.31 WEI (Browse shelf(Opens below)) Available E11956
Total holds: 0

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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