Free Download Georgina Barton, "Kinaesthetic Learning in Early Childhood"
English | ISBN: 1032215186 | 2023 | 180 pages | EPUB, PDF | 2 MB + 16 MB
Strongly grounded in research and rich with practical examples for educators, this book demonstrates the importance and benefits of kinaesthetic learning in young children's learning and development.

Free Download Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games
English | 2024 | ISBN: 3031452518 | 287 Pages | PDF EPUB (True) | 28 MB
Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games develops its specific learning techniques, motivated by application to autonomous driving and microgrid systems, with breadth and depth: integral reinforcement learning (RL) achieves model-free control without system estimation compared with system identification methods and their inevitable estimation errors; novel inverse RL methods fill a gap that will help them to attract readers interested in finding data-driven model-free solutions for inverse optimization and optimal control, imitation learning and autonomous driving among other areas.

Free Download Hands-On Machine Learning with Scikit-Learn and TensorFlow By Aurélien Géron
2017 | 568 Pages | ISBN: 9352135210 | PDF | 8 MB
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks-scikit-learn and TensorFlow-author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural nets Use scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets Apply practical code examples without acquiring excessive machine learning theory or algorithm details

Free Download For the sake of learning: essays in honor of Anthony Grafton By Ann Blair, Anja-Silvia Goeing (editors)
2016 | 1172 Pages | ISBN: 9004263306 | PDF | 20 MB
In this tribute to Anthony Grafton, fifty-eight contributors present new research across the many areas in which Grafton has been active in the history of scholarship and learned culture.

Free Download Federated Learning for Future Intelligent Wireless Networks
English | 2024 | ISBN: 1119913896 | 306 Pages | PDF | 8 MB
In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy.

Free Download Martin L Maehr, "Encouraging a Continuing Personal Investment in Learning: Motivation as an Instructional Outcome "
English | ISBN: 1617357146 | 2012 | 80 pages | PDF | 2 MB
The writing of this book was in part supported by a grant from the National Science Foundation (NSFEHR 0335369). It represents a significant extension and enriched interpretation of earlier work on "motivation as an instructional outcome" (e.g., Maehr, 1976). Such enrichment and enhancement was prompted by the work on the project as it was conceptualized and envisioned by Paul Pintrich--and later, following his untimely death, carried out by a cadre of students and colleagues, including especially his Wife, Life Partner and also oft-time collaborator in multiple research and scholarly endeavors: Dr. Elizabeth DeGroot as well as several colleagues, including, the author of this volume and Dr. Stuart Karabenick. Of course, it is the primary author of this volume who must bear the responsibility for omissions, errors and interpretations that may have slipped into the text. But whatever portions of this volume may be deemed worthy of consideration and possibly of some value for fellow scholars presently or in the future -- and also contribute in at least some small way not only to continuing scholarly study of "The Most important attitude that can be formed: "That of Desire to go on Learning." But therewith here and there also prove useful not only for scholars and the development of an increased understanding of the nature and nurture of motivation and its impact on the pursuit of knowledge but also prove useful to students in preparing to become educators-- and perhaps also of value to experienced educational practitioners -- and here there maybe also to parents and others with a concern for the nature and nurture of excellence in teaching and learning.

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