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Machine learning : theoretical foundations and practical applications
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ISBN: 9813365188 981336517X Year: 2021 Publisher: Singapore : Springer,

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Topics include neural network learning, knowledge acquisition and learning, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.


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Deep learning through sparse and low-rank modeling
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ISBN: 9780128136607 012813660X 0128136596 9780128136591 Year: 2019 Publisher: London : Academic Press,

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Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models—those that emphasize problem-specific Interpretability—with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with the sparse/low rank methods and algorithms, providing a rich variety of theoretical and analytic tools to guide the design and interpretation of deep learning models. The development of the theory and models is supported by a wide variety of applications in computer vision, machine learning, signal processing, and data mining. This book will be highly useful for researchers, graduate students and practitioners working in the fields of computer vision, machine learning, signal processing, optimization and statistics. Combines classical sparse and low-rank models and algorithms with the latest advances in deep learning networks Shows how the structure and algorithms of sparse and low-rank methods improves the performance and interpretability of Deep Learning models Provides tactics on how to build and apply customized deep learning models for various applications


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Deep learning for data analytics : foundations, biomedical applications, and challenges
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ISBN: 9780128226087 0128226080 9780128197646 0128197641 Year: 2020 Publisher: London, England : Academic Press,

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Device-to-device-based proximity service : architecture, issues, and applications
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ISBN: 152311360X 1351646516 1315120208 1498724183 Year: 2017 Publisher: Boca Raton : Taylor & Francis, CRC Press,

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"D2D-based proximity service is a very hot topic with great commercial potential from an application standpoint. Unlike existing books which focus on D2D communications technologies, this book fills a gap by summarizing and analyzing the latest applications and research results in academic, industrial fields, and standardization. The authors present the architecture, fundamental issues, and applications in a D2D networking environment from both application and interdisciplinary points of view."--Provided by publisher.


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Machine learning with tensorflow 1.x : second generation machine learning with googles brainchild tensorflow 1.x
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Year: 2017 Publisher: Birmingham, England ; Mumbai, [India] : Packt,

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Tackle common commercial machine learning problems with Google's TensorFlow 1.x library and build deployable solutions. About This Book Enter the new era of second-generation machine learning with Python with this practical and insightful guide Set up TensorFlow 1.x for actual industrial use, including high-performance setup aspects such as multi-GPU support Create pipelines for training and using applying classifiers using raw real-world data Who This Book Is For This book is for data scientists and researchers who are looking to either migrate from an existing machine learning library or jump into a machine learning platform headfirst. The book is also for software developers who wish to learn deep learning by example. Particular focus is placed on solving commercial deep learning problems from several industries using TensorFlow's unique features. No commercial domain knowledge is required, but familiarity with Python and matrix math is expected. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build deep neural networks using TensorFlow 1.x Cover key tasks such as clustering, sentiment analysis, and regression analysis using TensorFlow 1.x Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Learn how to use multiple GPUs for faster training using AWS In Detail Google's TensorFlow is a game changer in the world of machine learning. It has made machine learning faster, simpler, and more accessible than ever before. This book will teach you how to easily get started with machine learning using the power of Python and TensorFlow 1.x. Firstly, you'll cover the basic installation procedure and explore the capabilities of TensorFlow 1.x. This is followed by training and running the first classifier, and coverage of the unique features of the library including data flow graphs, training, and the visualization of performance with TensorBoard - all within an example-rich context using problems from multiple industries. You'll be able to further explore text and image analysis, and be introduced to CNN models and their setup in TensorFlow 1.x. Next, you'll implement a complete real-life production system from training to serving a deep learning model. As you advance you'll learn about Amazon Web Services (AWS) and create a deep...


Book
Information management and machine intelligence : proceedings of ICIMMI 2019
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ISBN: 9811549362 9811549354 Year: 2021 Publisher: Springer Singapore

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This book features selected papers presented at the International Conference on Information Management and Machine Intelligence (ICIMMI 2019), held at the Poornima Institute of Engineering & Technology, Jaipur, Rajasthan, India, on December 14–15, 2019. It covers a range of topics, including data analytics; AI; machine and deep learning; information management, security, processing techniques and interpretation; applications of artificial intelligence in soft computing and pattern recognition; cloud-based applications for machine learning; application of IoT in power distribution systems; as well as wireless sensor networks and adaptive wireless communication.

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Machine learning


Book
Deep learning applications.
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ISBN: 981156759X 9811567581 Year: 2021 Publisher: Springer Singapore

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This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

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Machine learning


Book
Machine learning technologies and applications : proceedings of ICACECS 2020
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ISBN: 9813340460 9813340452 Year: 2021 Publisher: Gateway East, Singapore : Springer,

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Enabling machine learning applications in data science : proceedings of Arab Conference for Emerging Technologies 2020
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ISBN: 9813361298 981336128X Year: 2021 Publisher: Gateway East, Singapore : Springer,

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Machine learning, deep learning and computational intelligence for wireless communication : proceedings of MDCWC 2020
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ISBN: 9811602891 9811602883 Year: 2021 Publisher: Gateway East, Singapore : Springer,

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