Pro Deep Learning With Tensorflow 2 0
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Pro Deep Learning With Tensorflow
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Author : Santanu Pattanayak
language : en
Publisher: Apress
Release Date : 2017-12-06
Pro Deep Learning With Tensorflow written by Santanu Pattanayak and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-06 with Computers categories.
Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFlow provides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deep learning applications. The code presented in the book is available in the form of iPython notebooks and scripts which allow you to try out examples and extend them in interesting ways. You will be equipped with the mathematical foundation and scientific knowledge to pursue research in this field and give back to the community. What You'll Learn Understand full stack deep learning using TensorFlow and gain a solid mathematical foundation for deep learning Deploy complex deep learning solutions in production using TensorFlow Carry out research on deep learning and perform experiments using TensorFlow Who This Book Is For Data scientists and machine learning professionals, software developers, graduate students, and open source enthusiasts
Pro Deep Learning With Tensorflow 2 0
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Author : Santanu Pattanayak
language : en
Publisher: Apress
Release Date : 2023-01-01
Pro Deep Learning With Tensorflow 2 0 written by Santanu Pattanayak and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Computers categories.
This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2.0. Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you will learn about convolutional neural networks, including new convolutional methods such as dilated convolution, depth-wise separable convolution, and their implementation. You’ll then gain an understanding of natural language processing in advanced network architectures such as transformers and various attention mechanisms relevant to natural language processing and neural networks in general. As you progress through the book, you’ll explore unsupervised learning frameworks that reflect the current state of deep learning methods, such as autoencoders and variational autoencoders. The final chapter covers the advanced topic of generative adversarial networks and their variants, such as cycle consistency GANs and graph neural network techniques such as graph attention networks and GraphSAGE. Upon completing this book, you will understand the mathematical foundations and concepts of deep learning, and be able to use the prototypes demonstrated to build new deep learning applications. What You Will Learn Understand full-stack deep learning using TensorFlow 2.0 Gain an understanding of the mathematical foundations of deep learning Deploy complex deep learning solutions in production using TensorFlow 2.0 Understand generative adversarial networks, graph attention networks, and GraphSAGE Who This Book Is For: Data scientists and machine learning professionals, software developers, graduate students, and open source enthusiasts.
Deep Learning And Its Applications Using Python
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Author : Niha Kamal Basha
language : en
Publisher: John Wiley & Sons
Release Date : 2023-10-31
Deep Learning And Its Applications Using Python written by Niha Kamal Basha and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-31 with Computers categories.
This book thoroughly explains deep learning models and how to use Python programming to implement them in applications such as NLP, face detection, face recognition, face analysis, and virtual assistance (chatbot, machine translation, etc.). It provides hands-on guidance in using Python for implementing deep learning application models. It also identifies future research directions for deep learning.
Artificial Intelligence And Image Processing In Medical Imaging
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Author : Walid A. Zgallai
language : en
Publisher: Elsevier
Release Date : 2024-01-18
Artificial Intelligence And Image Processing In Medical Imaging written by Walid A. Zgallai and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-18 with Science categories.
Artificial Intelligence and Image Processing in Medical Imaging deals with the applications of processing medical images with a view of improving the quality of the data in order to facilitate better decision- making. The book covers the basics of medical imaging and the fundamentals of image processing. It explains spatial and frequency domain applications of image processing, introduces image compression techniques and their applications, and covers image segmentation techniques and their applications. The book includes object detection and classification applications and provides an overall background to statistical analysis in biomedical systems. The role of Machine Learning, including Neural Networks, Deep Learning, and the implications of the expansion of artificial intelligence is also covered. With contributions from prominent researchers worldwide, this book provides up-to-date and comprehensive coverage of AI applications in image processing where readers will find the latest information with clear examples and illustrations. - Provides the latest comprehensive coverage of the developments of AI techniques and the principles of medical imaging - Covers all aspects of medical imaging, from acquisition, the use of hardware and software, image analysis and implementation of AI in problem solving - Provides examples of medical imaging and how they're processed, including segmentation, classification, and detection
Computational Intelligence In Engineering Science
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Author : Ngoc Thanh Nguyen
language : en
Publisher: Springer Nature
Release Date : 2025-07-22
Computational Intelligence In Engineering Science written by Ngoc Thanh Nguyen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-22 with Computers categories.
This four-volume set constitutes the refereed proceedings of the First International Conference on on Computational Intelligence in Engineering Science, ICCIES 2025, in Ho Chi Minh City, Vietnam, during July 23–25, 2025. The 115 full papers presented in these proceedings were carefully reviewed and selected from 210 submissions. The papers are organized in the following topical sections: Part I: Machine Learning; Wireless Networks (6G) Part II: Computer Vision; Natural Language Processing Part III: Intelligent Systems; Internet of Things Part IV: Machine Learning; Control Systems
Hands On Computer Vision With Tensorflow 2
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Author : Benjamin Planche
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-30
Hands On Computer Vision With Tensorflow 2 written by Benjamin Planche 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 2019-05-30 with Computers categories.
A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more Key FeaturesDiscover how to build, train, and serve your own deep neural networks with TensorFlow 2 and KerasApply modern solutions to a wide range of applications such as object detection and video analysisLearn how to run your models on mobile devices and web pages and improve their performanceBook Description Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learnCreate your own neural networks from scratchClassify images with modern architectures including Inception and ResNetDetect and segment objects in images with YOLO, Mask R-CNN, and U-NetTackle problems faced when developing self-driving cars and facial emotion recognition systemsBoost your application's performance with transfer learning, GANs, and domain adaptationUse recurrent neural networks (RNNs) for video analysisOptimize and deploy your networks on mobile devices and in the browserWho this book is for If you're new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you're an expert curious about the new TensorFlow 2 features, you'll find this book useful. While some theoretical concepts require knowledge of algebra and calculus, the book covers concrete examples focused on practical applications such as visual recognition for self-driving cars and smartphone apps.
Learn Tensorflow 2 0
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Author : Pramod Singh
language : en
Publisher: Apress
Release Date : 2019-12-17
Learn Tensorflow 2 0 written by Pramod Singh and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-17 with Computers categories.
Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build models using customer estimators. Further, it explains how to use TensorFlow 2.0 API to build machine learning and deep learning models for image classification using the standard as well as custom parameters. You'll review sequence predictions, saving, serving, deploying, and standardized datasets, and then deploy these models to production. All the code presented in the book will be available in the form of executable scripts at Github which allows you to try out the examples and extend them in interesting ways. What You'll Learn Review the new features of TensorFlow 2.0 Use TensorFlow 2.0 to build machine learning and deep learning models Perform sequence predictions using TensorFlow 2.0 Deploy TensorFlow 2.0 models with practical examples Who This Book Is For Data scientists, machine and deep learning engineers.
Mastering Deep Learning With Tensorflow From Fundamentals To Real World Deployment
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Author : Peter Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-17
Mastering Deep Learning With Tensorflow From Fundamentals To Real World Deployment written by Peter Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-17 with Computers categories.
Explore the realm of artificial intelligence with "Mastering Deep Learning with TensorFlow: From Fundamentals to Real-World Deployment." This all-encompassing guide provides an in-depth understanding of AI, machine learning, and deep learning, powered by TensorFlow—Google's leading AI framework. Whether you're a beginner starting your AI journey or a professional looking to elevate your expertise in AI model deployment, this book is tailored to meet your needs. Covering crucial topics like neural network design, convolutional and recurrent neural networks, natural language processing, and computer vision, it offers a robust introduction to TensorFlow and its AI applications. Through hands-on examples and a focus on practical solutions, you'll learn how to apply TensorFlow to solve real-world challenges. From theoretical foundations to deployment techniques, "Mastering Deep Learning with TensorFlow" takes you through every step, preparing you to build, fine-tune, and deploy advanced AI models. By the end, you’ll be ready to harness TensorFlow’s full potential, making strides in the rapidly evolving field of artificial intelligence. This book is an indispensable resource for anyone eager to engage with or advance in AI.
Advancement Of Deep Learning And Its Applications In Object Detection And Recognition
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Author : Roohie Naaz Mir
language : en
Publisher: CRC Press
Release Date : 2023-05-10
Advancement Of Deep Learning And Its Applications In Object Detection And Recognition written by Roohie Naaz Mir and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-10 with Computers categories.
Object detection is a basic visual identification problem in computer vision that has been explored extensively over the years. Visual object detection seeks to discover objects of specific target classes in a given image with pinpoint accuracy and apply a class label to each object instance. Object recognition strategies based on deep learning have been intensively investigated in recent years as a result of the remarkable success of deep learning-based image categorization. In this book, we go through in detail detector architectures, feature learning, proposal generation, sampling strategies, and other issues that affect detection performance. The book describes every newly proposed novel solution but skips through the fundamentals so that readers can see the field's cutting edge more rapidly. Moreover, unlike prior object detection publications, this project analyses deep learning-based object identification methods systematically and exhaustively, and also gives the most recent detection solutions and a collection of noteworthy research trends. The book focuses primarily on step-by-step discussion, an extensive literature review, detailed analysis and discussion, and rigorous experimentation results. Furthermore, a practical approach is displayed and encouraged.
Natural Language Processing And Applications
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Author : Huaping Zhang
language : en
Publisher: Springer Nature
Release Date : 2025-03-11
Natural Language Processing And Applications written by Huaping Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-11 with Computers categories.
This book gives a comprehensive introduction to natural language processing (NLP) and its applications, covering the topics of multimodal data processing, Chinese word segmentation, new word discovery, named entity recognition, keyword analysis, and knowledge graph construction in terms of semantic analysis. The inaugural chapter provides an overview of NLP, and the subsequent chapters delve into the foundations of artificial intelligence, covering traditional deep learning algorithms and platforms. The book then evolves to showcase the latest advancements in deep learning, addressing bottlenecks and unfolding developments from data-oriented, training-oriented, and application-oriented perspectives. Part II of the book navigates the practical applications of intelligent language processing. From web crawlers and multi-format document parsing to speech text recognition, readers gain insights into real-world scenarios. Each chapter provides examples and analyses, empowering readers to bridge theoretical knowledge with hands-on application, unlocking the transformative potential of AI through intelligent language processing. This book serves as a comprehensive resource for researchers, graduate students, and undergraduates in the field of natural language processing. Additionally, it offers valuable insights as a reference for engineers, technicians, and enthusiasts interested in the realm of big data intelligence. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.