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Author
Publisher
O'Reilly Media, Incorporated
Pub. Date
2019.
Edition
First edition.
Physical Desc
1 online resource (250 pages)
Language
English
Description
As Deep Neural Networks (DNNs) become increasingly common in real-world applications, the potential to "fool" them presents a new attack vector. In this book, author Katy Warr examines the security implications of how DNNs interpret audio and images very differently to humans. You'll learn about the motivations attackers have for exploiting flaws in DNN algorithms and how to assess the threat to systems incorporating neural network technology. Through...
6) Avoiding the pitfalls of deep learning: solving model overfitting with regularization and dropout
Author
Publisher
O'Reilly Media
Pub. Date
[2017]
Physical Desc
1 online resource (1 streaming video file (47 min., 16 sec.))
Language
English
Description
"Understanding how to create a deep learning neural network is an essential component of any data scientist's knowledge base. This course covers some of the challenges that arise when training neural networks. It focuses on the problem of overfitting and its potential remedy: regularization."--Resource description page
Publisher
O'Reilly Media, Inc
Pub. Date
2023.
Edition
[First edition].
Physical Desc
1 online resource (1 video file (2 hr., 53 min.)) : sound, color.
Language
English
Description
TensorFlow ( tf ) is a mainstream software platform for data science, data engineering, and MLOps. Maintained by Google and the community, this open source platform has facilitated many of the dramatic advances in AI over the past ten years. TensorFlow is used extensively across academia and industry, and is one of the most prominent tools in a data scientist's utility belt today. In this course you'll learn about TensorFlow itself and how to use...
Publisher
Academic Press
Pub. Date
2021.
Physical Desc
1 online resource (xvii, 288 pages) : illustrations.
Language
English
Description
Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications,...
Author
Publisher
Butterworth-Heinemann is an imprint of Elsevier
Pub. Date
[2015].
Physical Desc
1 online resource.
Language
English
Description
AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book! Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that...
Author
Publisher
Apress
Pub. Date
[2018]
Physical Desc
1 online resource : illustrations
Language
English
Description
"Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network. There are no prerequisites here and you won't see a single line of computer code in this book. Instead, it takes a hardware approach using very simple electronic components. You'll start off with an interesting non-technical...
Author
Publisher
Packt Publishing Ltd
Pub. Date
2018.
Physical Desc
1 online resource (1 volume) : illustrations
Language
English
Description
Create and unleash the power of neural networks by implementing C# and .Net code Key Features Get a strong foundation of neural networks with access to various machine learning and deep learning libraries Real-world case studies illustrating various neural network techniques and architectures used by practitioners Cutting-edge coverage of Deep Networks, optimization algorithms, convolutional networks, autoencoders and many more Book Description Neural...
Author
Publisher
O'Reilly Media
Pub. Date
[2017]
Physical Desc
1 online resource (1 streaming video file (55 min., 13 sec.))
Language
English
Description
"Deep learning neural networks have driven breakthrough results in computer vision, speech processing, machine translation, and reinforcement learning. As a result, neural networks have become an essential part of any data scientist's toolkit. This course explains what neural networks are, why they are powerful algorithms, and why they have a particular structure. It begins by introducing the core components of a neural network (i.e., nodes, weights,...
Author
Publisher
Apress
Pub. Date
[2019]
Physical Desc
1 online resource
Language
English
Description
Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get...
Author
Publisher
Manning Publications
Pub. Date
2021.
Edition
[First edition].
Physical Desc
1 online resource (1 audio file (13 hr., 43 min.))
Language
English
Description
One of the best deep learning books I have read. Muhammad Sohaib Arif, Tek Systems Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patterns and Practices you will find: Internal functioning of modern convolutional neural networks Procedural reuse design pattern for CNN architectures Models for mobile and IoT devices Assembling large-scale model...
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