Exploring Neural Networks With C
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Exploring Neural Networks With C
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Author : Ryszard Tadeusiewicz
language : en
Publisher: CRC Press
Release Date : 2017-07-27
Exploring Neural Networks With C written by Ryszard Tadeusiewicz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-27 with Computers categories.
The utility of artificial neural network models lies in the fact that they can be used to infer functions from observations making them especially useful in applications where the complexity of data or tasks makes the design of such functions by hand impractical.Exploring Neural Networks with C# presents the important properties of neural networks
Exploring Neural Networks With C
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Author : Ryszard Tadeusiewicz
language : en
Publisher: CRC Press
Release Date : 2014-09-02
Exploring Neural Networks With C written by Ryszard Tadeusiewicz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-02 with Computers categories.
The utility of artificial neural network models lies in the fact that they can be used to infer functions from observations—making them especially useful in applications where the complexity of data or tasks makes the design of such functions by hand impractical. Exploring Neural Networks with C# presents the important properties of neural networks—while keeping the complex mathematics to a minimum. Explaining how to build and use neural networks, it presents complicated information about neural networks structure, functioning, and learning in a manner that is easy to understand. Taking a "learn by doing" approach, the book is filled with illustrations to guide you through the mystery of neural networks. Examples of experiments are provided in the text to encourage individual research. Online access to C# programs is also provided to help you discover the properties of neural networks. Following the procedures and using the programs included with the book will allow you to learn how to work with neural networks and evaluate your progress. You can download the programs as both executable applications and C# source code from http://home.agh.edu.pl/~tad//index.php?page=programy&lang=en
Elements Of Deep Learning For Computer Vision
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Author : Bharat Sikka
language : en
Publisher: BPB Publications
Release Date : 2021-06-24
Elements Of Deep Learning For Computer Vision written by Bharat Sikka and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-24 with Computers categories.
Conceptualizing deep learning in computer vision applications using PyTorch and Python libraries. KEY FEATURES ● Covers a variety of computer vision projects, including face recognition and object recognition such as Yolo, Faster R-CNN. ● Includes graphical representations and illustrations of neural networks and teaches how to program them. ● Includes deep learning techniques and architectures introduced by Microsoft, Google, and the University of Oxford. DESCRIPTION Elements of Deep Learning for Computer Vision gives a thorough understanding of deep learning and provides highly accurate computer vision solutions while using libraries like PyTorch. This book introduces you to Deep Learning and explains all the concepts required to understand the basic working, development, and tuning of a neural network using Pytorch. The book then addresses the field of computer vision using two libraries, including the Python wrapper/version of OpenCV and PIL. After establishing and understanding both the primary concepts, the book addresses them together by explaining Convolutional Neural Networks(CNNs). CNNs are further elaborated using top industry standards and research to explain how they provide complicated Object Detection in images and videos, while also explaining their evaluation. Towards the end, the book explains how to develop a fully functional object detection model, including its deployment over APIs. By the end of this book, you are well-equipped with the role of deep learning in the field of computer vision along with a guided process to design deep learning solutions. WHAT YOU WILL LEARN ● Get to know the mechanism of deep learning and how neural networks operate. ● Learn to develop a highly accurate neural network model. ● Access to rich Python libraries to address computer vision challenges. ● Build deep learning models using PyTorch and learn how to deploy using the API. ● Learn to develop Object Detection and Face Recognition models along with their deployment. WHO THIS BOOK IS FOR This book is for the readers who aspire to gain a strong fundamental understanding of how to infuse deep learning into computer vision and image processing applications. Readers are expected to have intermediate Python skills. No previous knowledge of PyTorch and Computer Vision is required. TABLE OF CONTENTS 1. An Introduction to Deep Learning 2. Supervised Learning 3. Gradient Descent 4. OpenCV with Python 5. Python Imaging Library and Pillow 6. Introduction to Convolutional Neural Networks 7. GoogLeNet, VGGNet, and ResNet 8. Understanding Object Detection 9. Popular Algorithms for Object Detection 10. Faster RCNN with PyTorch and YoloV4 with Darknet 11. Comparing Algorithms and API Deployment with Flask 12. Applications in Real World
Exploring Artificial Intelligence A Student S Handbook
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Author : Dr Thiyagarajan Sivaprakasam
language : en
Publisher: THIYAGARAJAN SIVAPRAKASAM
Release Date : 2024-05-15
Exploring Artificial Intelligence A Student S Handbook written by Dr Thiyagarajan Sivaprakasam and has been published by THIYAGARAJAN SIVAPRAKASAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-15 with Computers categories.
Exploring Artificial intelligence: A Student’s Handbook is a comprehensive educational guide designed to demystify Al for students, covering foundational theories and practical applications across twenty chapters. It progresses from basic machine learning algorithms to advanced topics, incorporating interactive quizzes, “Did You Know?” facts, and real-world examples to enrich learning. The book emphasizes hands-on interaction with Al through step-by-step activities, aiming to bridge theory and practice. It also addresses the ethical, societal, and futuristic aspects of Al, encouraging readers to consider the broader implications of Al technologies. This handbook serves as a foundational resource for aspiring Al enthusiasts, researchers, and practitioners, fostering a deeper understanding of Al’s impact on the future.
Hands On Neural Network Programming With C
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Author : Matt R. Cole
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-09-29
Hands On Neural Network Programming With C written by Matt R. Cole and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-29 with Computers categories.
Create and unleash the power of neural networks by implementing C# and .Net code Key FeaturesGet a strong foundation of neural networks with access to various machine learning and deep learning librariesReal-world case studies illustrating various neural network techniques and architectures used by practitionersCutting-edge coverage of Deep Networks, optimization algorithms, convolutional networks, autoencoders and many moreBook Description Neural networks have made a surprise comeback in the last few years and have brought tremendous innovation in the world of artificial intelligence. The goal of this book is to provide C# programmers with practical guidance in solving complex computational challenges using neural networks and C# libraries such as CNTK, and TensorFlowSharp. This book will take you on a step-by-step practical journey, covering everything from the mathematical and theoretical aspects of neural networks, to building your own deep neural networks into your applications with the C# and .NET frameworks. This book begins by giving you a quick refresher of neural networks. You will learn how to build a neural network from scratch using packages such as Encog, Aforge, and Accord. You will learn about various concepts and techniques, such as deep networks, perceptrons, optimization algorithms, convolutional networks, and autoencoders. You will learn ways to add intelligent features to your .NET apps, such as facial and motion detection, object detection and labeling, language understanding, knowledge, and intelligent search. Throughout this book, you will be working on interesting demonstrations that will make it easier to implement complex neural networks in your enterprise applications. What you will learnUnderstand perceptrons and how to implement them in C#Learn how to train and visualize a neural network using cognitive servicesPerform image recognition for detecting and labeling objects using C# and TensorFlowSharpDetect specific image characteristics such as a face using Accord.NetDemonstrate particle swarm optimization using a simple XOR problem and EncogTrain convolutional neural networks using ConvNetSharpFind optimal parameters for your neural network functions using numeric and heuristic optimization techniques.Who this book is for This book is for Machine Learning Engineers, Data Scientists, Deep Learning Aspirants and Data Analysts who are now looking to move into advanced machine learning and deep learning with C#. Prior knowledge of machine learning and working experience with C# programming is required to take most out of this book
Neurorobotics Explores Machine Learning
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Author : Fei Chen
language : en
Publisher: Frontiers Media SA
Release Date : 2023-01-20
Neurorobotics Explores Machine Learning written by Fei Chen and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Science categories.
Artificial Intelligence And Soft Computing
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Author : Leszek Rutkowski
language : en
Publisher: Springer
Release Date : 2017-06-01
Artificial Intelligence And Soft Computing written by Leszek Rutkowski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-01 with Computers categories.
The two-volume set LNAI 10245 and LNAI 10246 constitutes the refereed proceedings of the 16th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2017, held in Zakopane, Poland in June 2017. The 133 revised full papers presented were carefully reviewed and selected from 274 submissions. The papers included in the second volume are organized in the following five parts: data mining; artificial intelligence in modeling, simulation and control; various problems of artificial intelligence; special session: advances in single-objective continuous parameter optimization with nature-inspired algorithms; special session: stream data mining.
Ai Adventures Explore The Future
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Author : Ing. Barbora Štětinová MBA
language : en
Publisher: Barbora Štětinová
Release Date : 2024-01-01
Ai Adventures Explore The Future written by Ing. Barbora Štětinová MBA and has been published by Barbora Štětinová this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-01 with Games & Activities categories.
Discover the Fascinating World of Artificial Intelligence! AI Advantures: Explore the Future - book about AI for Kids is an exciting and engaging guide that takes young readers on an adventure into the amazing world of technology! Step by step, this book introduces children to the basics of computers, how Machine Learning and Artificial Intelligence (AI) is changing our world. Written by Barbora Štetinová, with insights from her son Matthew, this book combines technical understanding with youthful creativity to make complex ideas simple and fun.Kids will learn how AI learns, explore the secrets of neural networks, and discover how to use tools like ChatGPT. Whether your child is curious about IT or wants to understand how AI works, this book offers a clear and enjoyable path into the heart of modern technology.This book is ideal for young tech enthusiasts who want to explore machine learning, artificial neural networks or understand the safety of AI, and discover the vast possibilities it offers.Start your journey with AI for Kids and unlock the limitless potential that technology brings!
Exploring Service Science
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Author : Henriqueta Nóvoa
language : en
Publisher: Springer Nature
Release Date : 2020-01-27
Exploring Service Science written by Henriqueta Nóvoa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-27 with Computers categories.
This book constitutes the proceedings of the 10th International Conference on Exploring Service Science, IESS 2020, held in Porto, Portugal, in February 2020. The 28 papers presented in this volume were carefully reviewed and selected from 42 submissions. The book includes papers that extend the view on different concepts related to the development of the Service Science domain of study, applying them to frameworks, advanced technologies, and tools for the design of new, digitally-enabled service systems. This book is structured in six parts, based on the six main conference themes, as follows: Customer Experience, Data Analytics in Service, Emerging Service Technologies, Service Design and Innovation, Service Ecosystems, and Service Management.
Exploration Of Cortical Function
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Author : M. Stetter
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Exploration Of Cortical Function written by M. Stetter and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Medical categories.
Exploration of Cortical Function summarizes recent research efforts aiming at the revelation of cortical population coding and signal processing strategies. Topics include optical detection techniques of population activity in the sub-millimeter range, advanced methods for the statistical analysis of these data, and biologically inspired neuronal modeling techniques for population activities in the frameworks of optimal coding, statistical learning theory, and mean-field recurrent networks. Exploration of Cortical Function is unique in that it covers one complete branch of population-based brain research ranging from techniques for data acquisition over data analysis up to modeling techniques for the quantification of functional principles. The volume covers an area which is of great current interest to researchers working on cerebral cortex. The combination of models and image analysis techniques to examine the activity of large cohorts of neurons is especially intriguing and prone to considerable error and debate.