Free Download Digitalization and Learning as a Worlding Practice
English | 2024 | ISBN: 0367142805 | 187 Pages | PDF (True) | 9.3 MB
The book explores how learning is not just an internalization of knowledge but a problem- oriented activity of engaging with the world, a process of both meaning making and world making. It raises a pivotal question: how can digital technologies help to expand and enrich learning as a collaborative worlding practice? It discusses the importance of digital artifacts in shaping students' learning experiences, discerning how they nourish meaningful engagement and where they pose a hindrance. The book also investigates the role of digitalization in transforming everyday life and learning activity of students, and how learners, teachers, and educators can approach these transformations critically and constructively. Based on an embodied, subject- and world- centered concept of learning, the book offers its readers a sophisticated understanding of the inner connection between digitalization and learning.

Free Download Designing Sustainable Communities: Learning From Village Homes By Michael Corbett; Michael N. Corbett; Robert L. Thayer
1999 | 254 Pages | ISBN: 1559636866 | PDF | 21 MB
The movement towards creating sustainable communities has gained increased prominence with approaches such as New Urbanism, yet there are few examples of the successes. This text offers an analysis of one such example: Village Homes outside Davis, California. The area offers features including extensive common areas and green space; community gardens, orchards and vineyeards; narrow streets; pedestrian and bike paths; solar homes; and an innovative ecological drainage system.

Free Download Deep Learning for Numerical Applications with SAS® By Henry Bequet
2018 | 234 Pages | ISBN: 1635266807 | PDF | 23 MB
Foreword by Oliver Schabenberger, PhD Executive Vice President, Chief Operating Officer and Chief Technology OfficerSAS Dive into deep learning! Machine learning and deep learning are ubiquitous in our homes and workplaces-from machine translation to image recognition and predictive analytics to autonomous driving. Deep learning holds the promise of improving many everyday tasks in a variety of disciplines. Much deep learning literature explains the mechanics of deep learning with the goal of implementing cognitive applications fueled by Big Data. This book is different. Written by an expert in high-performance analytics, Deep Learning for Numerical Applications with SAS® introduces a new field: Deep Learning for Numerical Applications (DL4NA). Contrary to deep learning, the primary goal of DL4NA is not to learn from data but to dramatically improve the performance of numerical applications by training deep neural networks. Deep Learning for Numerical Applications with SAS® presents deep learning concepts in SAS along with step-by-step techniques that allow you to easily reproduce the examples on your high-performance analytics systems. It also discusses the latest hardware innovations that can power your SAS programs: from many-core CPUs to GPUs to FPGAs to ASICs. This book assumes the reader has no prior knowledge of high-performance computing, machine learning, or deep learning. It is intended for SAS developers who want to develop and run the fastest analytics. In addition to discovering the latest trends in hybrid architectures with GPUs and FPGAS, readers will learn how to Use deep learning in SAS Speed up their analytics using deep learning Easily write highly parallel programs using the many task computing paradigms For sample material and supporting resources, please see the author's page. This book is part of the SAS Press program.

Free Download Deep Learning for Medical Image Analysis, 2nd Edition
by S. Kevin Zhou, Hayit Greenspan
English | 2023 | ISBN: 032385124X | 544 Pages | True PDF | 22 MB

Free Download Debugging Machine Learning Models with Python: Develop high-performance, low-bias, and explainable machine learning and deep learning models by Ali Madani, Stephen MacKinnon
English | September 15, 2023 | ISBN: 1800208588 | 344 pages | PDF | 28 Mb
Master reproducible ML and DL models with Python and PyTorch to achieve high performance, explainability, and real-world success

Free Download Data-Centric Machine Learning with Python:
The ultimate guide to engineering and deploying high-quality models based on good data
English | 2024 | ISBN: 1804618128 | 466 Pages | EPUB (True) | 13 MB

Free Download Data Analytics and Learning: Proceedings of DAL 2022
English | 2024 | ISBN: 9819963451 | 265 Pages | PDF EPUB (True) | 62 MB
This book presents new theories and working models in the areas of data analytics and learning. The papers included in this volume were presented at the second International Conference on Data Analytics and Learning (DAL 2022), which was organized by the Department of Computer Science & Engineering, Alva's Institute of Engineering & Technology, Moodbidri, Mangalore, Karnataka, India in association with the Department of Studies in Computer Science, University of Mysore, Mysuru, Karnataka, India. The areas covered include pattern recognition, image processing, deep learning, computer vision, data analytics, machine learning, artificial intelligence, and intelligent systems.

Free Download Communication Efficient Federated Learning for Wireless Networks
English | 2024 | ISBN: 3031512650 | 190 Pages | PDF EPUB (True) | 25 MB
This book provides a comprehensive study of Federated Learning (FL) over wireless networks. It consists of three main parts: (a) Fundamentals and preliminaries of FL, (b) analysis and optimization of FL over wireless networks, and © applications of wireless FL for Internet-of-Things systems. In particular, in the first part, the authors provide a detailed overview on widely-studied FL framework. In the second part of this book, the authors comprehensively discuss three key wireless techniques including wireless resource management, quantization, and over-the-air computation to support the deployment of FL over realistic wireless networks. It also presents several solutions based on optimization theory, graph theory and machine learning to optimize the performance of FL over wireless networks. In the third part of this book, the authors introduce the use of wireless FL algorithms for autonomous vehicle control and mobile edge computing optimization.

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English | ISBN: 1908066490 | 2011 | 164 pages | PDF | 5 MB
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Free Download Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfalls
English | 2024 | ISBN: 3031393546 | 836 Pages | PDF EPUB (True) | 35 MB
This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks.