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Author
Language
English
Formats
Description
"Generative modeling is one of the hottest topics in AI. It's now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders, generative adversarial networks (GANs), encoder-decoder models, and world...
Author
Publisher
O'Reilly Media, Incorporated
Pub. Date
2019.
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...
Author
Publisher
Manning
Pub. Date
[2019]
Language
English
Formats
Description
"Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare!"--...
Author
Publisher
Packt Publishing
Pub. Date
2019.
Language
English
Description
Implement neural network architectures by building them from scratch for multiple real-world applications. Key Features From scratch, build multiple neural network architectures such as CNN, RNN, LSTM in Keras Discover tips and tricks for designing a robust neural network to solve real-world problems Graduate from understanding the working details of neural networks and master the art of fine-tuning them Book Description This book will take you from...
Author
Publisher
Apress
Pub. Date
[2019]
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
Series
Publisher
O'Reilly Media, Inc
Pub. Date
2024.
Language
English
Description
These shortcuts delve into generative AI, where algorithms and models create synthetic data, detect anomalies, and help confirm statistical properties. They explore how generative AI is reshaping risk management, fraud detection, and data simulation, and they offer a unique synthesis of theory and practical applications.
Author
Publisher
Apress
Pub. Date
2020
Language
English
Description
Apply computer vision and machine learning concepts in developing business and industrial applications using a practical, step-by-step approach. The book comprises four main sections starting with setting up your programming environment and configuring your computer with all the prerequisites to run the code examples. Section 1 covers the basics of image and video processing with code examples of how to manipulate and extract useful information from...
Publisher
Academic Press
Pub. Date
2021.
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
Language
English
Description
Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will...
Author
Publisher
Academic Press
Pub. Date
2019.
Language
English
Description
Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class...
Author
Series
Publisher
O'Reilly Media, Inc
Pub. Date
[2024]
Language
English
Description
These shortcuts delve into generative AI, where algorithms and models create synthetic data, detect anomalies, and help confirm statistical properties. They explore how generative AI is reshaping risk management, fraud detection, and data simulation, and they offer a unique synthesis of theory and practical applications.
Author
Series
Publisher
Apress
Pub. Date
[2018]
Language
English
Description
Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a 'thought process' that is capable of learning abstract concepts built from simpler primitives. These models are especially useful for image processing applications. At each step Deep Belief Nets...
Author
Publisher
Packt Publishing Ltd
Pub. Date
2018.
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
Packt Publishing
Pub. Date
2021.
Language
English
Description
Harness the power of the easy-to-use, high-performance fastai framework to rapidly create complete deep learning solutions with few lines of code Key Features Discover how to apply state-of-the-art deep learning techniques to real-world problems Build and train neural networks using the power and flexibility of the fastai framework Use deep learning to tackle problems such as image classification and text classification Book Description fastai is...
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