Unnormalizing Education

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Unnormalizing Education

Author : Joseph R. Jones
Publisher : IAP
Page : 81 pages
File Size : 44,6 Mb
Release : 2014-06-01
Category : Education
ISBN : 9781623967086

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Unnormalizing Education by Joseph R. Jones Pdf

Recently, with the number of students from higher education and K-12 settings committing suicide, it is apparent that homophobia and homophobic bullying are tremendous problems in our schools and universities. However, educators are unclear about an appropriate process for addressing these challenges. In this book, Jones postulates that we must begin exploring the culture of educational environments as they relate to sexual difference, in order to begin conceptualizing ways in which we may begin to address homophobia and heteronormativity. To that end, this book addresses how educators (at all levels) must begin examining how their concepts about different sexual identities are "normalized" through socializing processes and schooling. In doing so, this book examines how individuals construct meanings about homophobia and hate language through "contextual oppositions, " how educational environments maintain a ''false tolerance" when claiming to be tolerant of different sexual identities, how a hierarchy of hate language exists in educational environments, among other issues related to creating safe places for all students. In essence, the book attempts to "un"normalize society's constructions of sexual identity by deconstructing the social norms.

Feather Boas, Black Hoodies, and John Deere Hats

Author : Joseph R. Jones
Publisher : Springer
Page : 10 pages
File Size : 51,7 Mb
Release : 2017-12-05
Category : Education
ISBN : 9789463512152

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Feather Boas, Black Hoodies, and John Deere Hats by Joseph R. Jones Pdf

In Feather Boas, Black Hoodies, and John Deere Hats, Jones once again challenges our beliefs about difference and acceptance. As one reviewer writes, “through a series of rich narratives, Jones provides examples of attitudes, experiences, and institutional acts that continue to propagate the marginalization of people in our communities. Intertwined within these stories are thoughtfully selected ideas to help us understand that embracing difference, and not merely respecting it, can be the catalyst for real change in all of us.” The book engenders a dialogic space for individuals to grapple with the idea of difference and the importance of inclusion in educational environments, and by extension broader society.

My Second First Year

Author : Joseph R. Jones
Publisher : IAP
Page : 99 pages
File Size : 49,5 Mb
Release : 2019-09-01
Category : Education
ISBN : 9781641137546

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My Second First Year by Joseph R. Jones Pdf

Dr. Jones returned to the high school classroom after 15 years in higher education, most recently as an Associate Dean. This text chronicles his journey into his new teaching career. The premise of the text is framed on the attributes of a relational pedagogy. As such, the book discusses the relationships that Dr. Jones developed throughout the academic year. In this capacity, relational pedagogy allows the reader a unique lens through which to view the schooling process in this metropolitan southern town. In the book, Jones examines topics such as standardized testing, racism, sexuality, cheating, among other topics, through a critical theory paradigm. In doing so, Jones is able to interweave theoretical concepts within the daily actions of the schooling process. As such, the text is a unique reconceptualization of schools and the purpose of schools. Praise for My Second First Year: "In My Second First Year, Dr. Jones discusses his experiences leaving academia and returning to a high school English classroom, a daunting task that few academics would attempt. As a biologist and without affiliation with a teacher preparation program, I can attest to the importance of Jones’ work. This text illuminates the educational process for millions of children, which allows those of us not in the daily trenches of teaching K-12 students to experience the reality of our educational process. His discussions of school shootings, testing, and marginalization of students can become a catalyst that causes everyone in society to begin reexamining how we educate our children. Jones’ book could become the commencement point for educational reform." Linda Hensel, PhD Mercer University "In My Second First Year, Dr. Jones discusses his journey leaving higher education to return to a high school classroom. His powerful depictions of the realities of standardized testing, school shootings, racism, sexuality, and other topics cause the reader to reflect on all aspects of how children are educated. His use of relational pedagogy as his framework reminds us of the importance of positive relationships in schools and society. This text is a must read for anyone who advocates for our children." Nila Burt, EdS Assistant Principal Northside High School Georgia "Many of the stories in My Second First Year will be familiar to many teachers working in American PK-12 public schools as they will be similar to their own experiences. Dr. Jones takes us on a journey that many of us in academia would be apprehensive to take. By providing example after example, he demonstrates the significance of relational pedagogy and how it can increase the likelihood of student success. In this climate of student-to-college discourse, Jones provides evidence on how positive relations between teacher and students benefit all students regardless of post-secondary plans. This is significant for at the end of the day, the goal of schooling is about more than whether or not our students find employment. It is more important that students grow into caring, lifelong learners who can find happiness regardless of occupational goals. Jones reminds us all why we became teachers in the first place and—for many—why many teachers choose to stay in the profession." Vincent Youngbauer, PhD Mercer University

Under the Bleachers

Author : Joseph R. Jones
Publisher : Springer
Page : 144 pages
File Size : 41,7 Mb
Release : 2015-06-17
Category : Education
ISBN : 9789463000406

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Under the Bleachers by Joseph R. Jones Pdf

“The field of education can be a rewarding, but ever challenging career. This book is an essential read for new teachers and veteran teachers alike. The insightful stories that Dr. Joseph Jones has masterfully chosen as part of the book will inspire a new sense of resolve and hope for those who are feeling the weight of seemingly impossible demands placed on teachers. These compelling excerpts will assist the reader through the maze of uncertainty that many new teachers face.” --Wendi West Veteran Teacher Elementary, Virginia Under the Bleachers: Teachers’ Reflections of What They Didn’t Learn in College is a unique text because the chapters offer insight into the daily chaos of teaching. The chapters are written by practicing educators and provide advice to both future educators and current teachers. It is important to mention, the text is not an avenue to criticize teacher education programs; rather, the book opens a dialogic space in which all educators can begin discussing and reflecting on the realities of the schooling process.

The Unnormalized Relational Data Model

Author : Hiroyuki Kitagawa,Tosiyasu L. Kunii
Publisher : Springer Science & Business Media
Page : 172 pages
File Size : 52,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9784431680994

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The Unnormalized Relational Data Model by Hiroyuki Kitagawa,Tosiyasu L. Kunii Pdf

Computer Science Workbench is a monograph series which will provide you with an in-depth working knowledge of current developments in computer technology. Every volume in this series will deal with a topic of importance in computer science and elaborate on how you yourself can build systems related to the main theme. You will be able to develop a variety of systems, including computer software tools, computer graphics, computer animation, database management systems, and computer-aided design and manufacturing systems. Computer Science Workbench represents an important new contribution in the field of practical computer technology. TOSIYASU L. KUNII Preface The evolution of database systems research is itself a story. Long after the emergence of systems derived from practical applications, Codd's relational data model has gradually occupied the theoretical domain of database systems and is moving into the realms of practical use. Certainly, the theoretical foundation makes database design, validation, and testing easier. However, Cod d's model allows only fiat tables to be handled, while most business and engineering data in practice are in nested table forms. Thus, a recent major obstacle in database systems development is the large gap between the theory and the practice.

Machine Learning & AI

Author : Prathmesh Yelne
Publisher : Codegyan
Page : 250 pages
File Size : 54,9 Mb
Release : 2023-08-01
Category : Education
ISBN : 8210379456XXX

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Machine Learning & AI by Prathmesh Yelne Pdf

Discover the extraordinary possibilities of machine learning and artificial intelligence in this groundbreaking exploration. From self-driving cars to virtual assistants, this book delves into the fascinating world of algorithms and how they are transforming industries and revolutionizing our lives. Explore the inner workings of neural networks, deep learning models, and predictive analytics, and witness the profound impact they have on decision-making, problem-solving, and data analysis. Whether you're a novice or an expert in the field, prepare to be captivated by the limitless potential of machine learning and AI.

Fundamentals of Deep Learning

Author : Nithin Buduma,Nikhil Buduma,Joe Papa
Publisher : "O'Reilly Media, Inc."
Page : 390 pages
File Size : 49,5 Mb
Release : 2022-05-16
Category : Computers
ISBN : 9781492082132

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Fundamentals of Deep Learning by Nithin Buduma,Nikhil Buduma,Joe Papa Pdf

We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics. The updated second edition of this book describes the intuition behind these innovations without jargon or complexity. Python-proficient programmers, software engineering professionals, and computer science majors will be able to reimplement these breakthroughs on their own and reason about them with a level of sophistication that rivals some of the best developers in the field. Learn the mathematics behind machine learning jargon Examine the foundations of machine learning and neural networks Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Explore methods in interpreting complex machine learning models Gain theoretical and practical knowledge on generative modeling Understand the fundamentals of reinforcement learning

Learning Theory

Author : John Shawe-Taylor,Yoram Singer
Publisher : Springer
Page : 654 pages
File Size : 41,7 Mb
Release : 2004-06-11
Category : Computers
ISBN : 9783540278191

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Learning Theory by John Shawe-Taylor,Yoram Singer Pdf

This book constitutes the refereed proceedings of the 17th Annual Conference on Learning Theory, COLT 2004, held in Banff, Canada in July 2004. The 46 revised full papers presented were carefully reviewed and selected from a total of 113 submissions. The papers are organized in topical sections on economics and game theory, online learning, inductive inference, probabilistic models, Boolean function learning, empirical processes, MDL, generalisation, clustering and distributed learning, boosting, kernels and probabilities, kernels and kernel matrices, and open problems.

Learning Theory

Author : Peter Auer
Publisher : Springer Science & Business Media
Page : 703 pages
File Size : 43,7 Mb
Release : 2005-06-20
Category : Computers
ISBN : 9783540265566

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Learning Theory by Peter Auer Pdf

This book constitutes the refereed proceedings of the 18th Annual Conference on Learning Theory, COLT 2005, held in Bertinoro, Italy in June 2005. The 45 revised full papers together with three articles on open problems presented were carefully reviewed and selected from a total of 120 submissions. The papers are organized in topical sections on: learning to rank, boosting, unlabeled data, multiclass classification, online learning, support vector machines, kernels and embeddings, inductive inference, unsupervised learning, generalization bounds, query learning, attribute efficiency, compression schemes, economics and game theory, separation results for learning models, and survey and prospects on open problems.

Artificial Neural Networks and Machine Learning – ICANN 2016

Author : Alessandro E.P. Villa,Paolo Masulli,Antonio Javier Pons Rivero
Publisher : Springer
Page : 567 pages
File Size : 44,6 Mb
Release : 2016-08-26
Category : Computers
ISBN : 9783319447780

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Artificial Neural Networks and Machine Learning – ICANN 2016 by Alessandro E.P. Villa,Paolo Masulli,Antonio Javier Pons Rivero Pdf

The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions. They were organized in topical sections named: from neurons to networks; networks and dynamics; higher nervous functions; neuronal hardware; learning foundations; deep learning; classifications and forecasting; and recognition and navigation. There are 47 short paper abstracts that are included in the back matter of the volume.

Machine Learning with R

Author : Brett Lantz
Publisher : Packt Publishing Ltd
Page : 763 pages
File Size : 55,6 Mb
Release : 2023-05-29
Category : Computers
ISBN : 9781801076050

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Machine Learning with R by Brett Lantz Pdf

Learn how to solve real-world data problems using machine learning and R Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features The 10th Anniversary Edition of the bestselling R machine learning book, updated with 50% new content for R 4.0.0 and beyond Harness the power of R to build flexible, effective, and transparent machine learning models Learn quickly with this clear, hands-on guide by machine learning expert Brett Lantz Book Description Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Fourth Edition, provides a hands-on, accessible, and readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to know for data pre-processing, uncovering key insights, making new predictions, and visualizing your findings. This 10th Anniversary Edition features several new chapters that reflect the progress of machine learning in the last few years and help you build your data science skills and tackle more challenging problems, including making successful machine learning models and advanced data preparation, building better learners, and making use of big data. You'll also find this classic R data science book updated to R 4.0.0 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Whether you're looking to take your first steps with R for machine learning or making sure your skills and knowledge are up to date, this is an unmissable read that will help you find powerful new insights in your data. What you will learn Learn the end-to-end process of machine learning from raw data to implementation Classify important outcomes using nearest neighbor and Bayesian methods Predict future events using decision trees, rules, and support vector machines Forecast numeric data and estimate financial values using regression methods Model complex processes with artificial neural networks Prepare, transform, and clean data using the tidyverse Evaluate your models and improve their performance Connect R to SQL databases and emerging big data technologies such as Spark, Hadoop, H2O, and TensorFlow Who this book is for This book is designed to help data scientists, actuaries, data analysts, financial analysts, social scientists, business and machine learning students, and any other practitioners who want a clear, accessible guide to machine learning with R. No R experience is required, although prior exposure to statistics and programming is helpful.

Machine Learning for Engineers

Author : Osvaldo Simeone
Publisher : Cambridge University Press
Page : 601 pages
File Size : 55,9 Mb
Release : 2022-09-30
Category : Computers
ISBN : 9781316512821

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Machine Learning for Engineers by Osvaldo Simeone Pdf

This self-contained introduction contains all students need to start applying machine learning principles to real-world engineering problems.

Artificial Neural Networks and Machine Learning – ICANN 2021

Author : Igor Farkaš,Paolo Masulli,Sebastian Otte,Stefan Wermter
Publisher : Springer Nature
Page : 617 pages
File Size : 53,9 Mb
Release : 2021-09-11
Category : Computers
ISBN : 9783030863623

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Artificial Neural Networks and Machine Learning – ICANN 2021 by Igor Farkaš,Paolo Masulli,Sebastian Otte,Stefan Wermter Pdf

The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as adversarial machine learning, anomaly detection, attention and transformers, audio and multimodal applications, bioinformatics and biosignal analysis, capsule networks and cognitive models. *The conference was held online 2021 due to the COVID-19 pandemic.

Removing the Margins

Author : George Jerry Sefa Dei
Publisher : Canadian Scholars’ Press
Page : 322 pages
File Size : 49,7 Mb
Release : 2000
Category : Education
ISBN : 9781551301532

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Removing the Margins by George Jerry Sefa Dei Pdf

Removing the Margins works to identify and challenge many of the cultural and systematic paradigms that perpetuate racism and other forms of oppression in mainstream schooling. The authors pursue the ideal that education should not simply affirm the status quo but should produce knowledge for social action. This philosophical and theoretical resource also moves beyond the study of educational failure to explore the new and creative ways schooling barriers have been confronted. The focus is placed on the factors of representation, family and community, staff equity, language integration and spirituality as fundamental to school reform. Removing the Margins is the product of five years of research and writing in the search for best practices in inclusive education. The authors address the philosophical and theoretical bases for inclusivity in this book, while laying out the practical approach in the accompanying volume Inclusive Schooling: A Teacher's Guide to Removing the Margins.

Active Machine Learning with Python

Author : Margaux Masson-Forsythe
Publisher : Packt Publishing Ltd
Page : 176 pages
File Size : 45,6 Mb
Release : 2024-03-29
Category : Computers
ISBN : 9781835462683

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Active Machine Learning with Python by Margaux Masson-Forsythe Pdf

Use active machine learning with Python to improve the accuracy of predictive models, streamline the data analysis process, and adapt to evolving data trends, fostering innovation and progress across diverse fields Key Features Learn how to implement a pipeline for optimal model creation from large datasets and at lower costs Gain profound insights within your data while achieving greater efficiency and speed Apply your knowledge to real-world use cases and solve complex ML problems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionBuilding accurate machine learning models requires quality data—lots of it. However, for most teams, assembling massive datasets is time-consuming, expensive, or downright impossible. Led by Margaux Masson-Forsythe, a seasoned ML engineer and advocate for surgical data science and climate AI advancements, this hands-on guide to active machine learning demonstrates how to train robust models with just a fraction of the data using Python's powerful active learning tools. You’ll master the fundamental techniques of active learning, such as membership query synthesis, stream-based sampling, and pool-based sampling and gain insights for designing and implementing active learning algorithms with query strategy and Human-in-the-Loop frameworks. Exploring various active machine learning techniques, you’ll learn how to enhance the performance of computer vision models like image classification, object detection, and semantic segmentation and delve into a machine AL method for selecting the most informative frames for labeling large videos, addressing duplicated data. You’ll also assess the effectiveness and efficiency of active machine learning systems through performance evaluation. By the end of the book, you’ll be able to enhance your active learning projects by leveraging Python libraries, frameworks, and commonly used tools.What you will learn Master the fundamentals of active machine learning Understand query strategies for optimal model training with minimal data Tackle class imbalance, concept drift, and other data challenges Evaluate and analyze active learning model performance Integrate active learning libraries into workflows effectively Optimize workflows for human labelers Explore the finest active learning tools available today Who this book is for Ideal for data scientists and ML engineers aiming to maximize model performance while minimizing costly data labeling, this book is your guide to optimizing ML workflows and prioritizing quality over quantity. Whether you’re a technical practitioner or team lead, you’ll benefit from the proven methods presented in this book to slash data requirements and iterate faster. Basic Python proficiency and familiarity with machine learning concepts such as datasets and convolutional neural networks is all you need to get started.