Utilizing Visuals and Information Technology in Mathematics Classrooms
Hiroto Namihira
Academic scholars face a difficult challenge when attempting to grasp the intricate world of mathematics. The complexity of mathematical concepts often lies hidden beneath layers of formulas and procedures, obscuring their true essence. Traditional educational resources often fall short in conveying the profound meaning behind these concepts, leaving students and scholars feeling overwhelmed and irritated. Furthermore, the integration of information technology (IT) with mathematics remains an under explored frontier, preventing the development of logical insights from arbitrary initial conditions. As a result, there is an urgent need for a solution that can bridge these gaps and offer an innovative approach to learning mathematics. Utilizing Visuals and Information Technology in Mathematics Classrooms is a comprehensive and innovative solution to the challenges faced by academic scholars in the field of mathematics. This book takes a bold step in addressing these issues by offering a unique approach – visualization. By harnessing the power of visual representation, we transform complex mathematical concepts into easily understandable images, making the transition from initial states to final states of these crucial ideas visually intuitive. Utilizing Visuals and Information Technology in Mathematics Classrooms not only simplifies the learning process but also sets the stage for a paradigm shift by effectively merging education and IT, creating a forward-thinking approach that is poised to reshape the world of academia.
- Format: Hardback
- ISBN: 9781668499870
- Publication Date: Apr 2024
- Availability: Not Yet Available - Pre-Order Now
Automated Deep Learning
Xuanyi Dong
Aimed at students and researchers, this monograph provides an evaluative overview of automated deep learning in the early 2020s, identifying where future opportunities for progress may exist.
- Format: Paperback
- ISBN: 9781638283188
- Publication Date: Feb 2024
- Availability: In Stock - Despatched Within 5 Working Days
AutonoML
David Jacob Kedziora
This monograph lays the groundwork for students and researchers to understand the factors limiting architectural integration, without which the field of automated ML risks stifling both its technical advantages and general uptake.
- Format: Paperback
- ISBN: 9781638283164
- Publication Date: Feb 2024
- Availability: In Stock - Despatched Within 5 Working Days
Causal Fairness Analysis
Drago Plečko
This monograph is a timely and important introduction to developing future AI systems incorporating inherent fairness and as such will be of wide interest not only to AI system designers, but all who are interested in the wider impact AI will have on society.
- Format: Paperback
- ISBN: 9781638283300
- Publication Date: Jan 2024
- Availability: In Stock - Despatched Within 5 Working Days
User-friendly Introduction to PAC-Bayes Bounds
Pierre Alquier
Covering both empirical and oracle PAC-bounds, this book serves as a primer for students and researchers who want to get to grips quickly with the subject.
- Format: Paperback
- ISBN: 9781638283263
- Publication Date: Jan 2024
- Availability: In Stock - Despatched Within 5 Working Days
A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists
Andrea Montanari
Written by two recognized experts and based on a course given at Stanford University, this tutorial is a unique introduction to a topic that has many avenues for furthering research in statistics, mathematics, and computer science. It provides an accessible tutorial to understand and use the theories being deployed in physics for over 50 years.
- Format: Paperback
- ISBN: 9781638282129
- Publication Date: Jan 2024
- Availability: In Stock - Despatched Within 5 Working Days
Reinforcement Learning, Bit by Bit
Xiuyuan Lu
This book will be of interest to students and researchers working in reinforcement learning and information theorists wishing to apply their knowledge in a practical way to reinforcement learning problems.
- Format: Paperback
- ISBN: 9781638282549
- Publication Date: Jul 2023
- Availability: In Stock - Despatched Within 5 Working Days
Tutorial on Amortized Optimization
Brandon Amos
This tutorial provides the reader with a complete source for understanding the theory behind and implementing amortized optimization in many machine learning applications. It will be of interest to students and practitioners alike.
- Format: Paperback
- ISBN: 9781638282082
- Publication Date: Jun 2023
- Availability: In Stock - Despatched Within 5 Working Days
Introduction to Riemannian Geometry and Geometric Statistics
Nicolas Guigui
Containing many practical Python examples, this monograph is a valuable resource both for mathematicians and applied scientists to learn the theory of Riemann geometry and its use in practice implemented with the Geomstats package where most of the difficulties are hidden under high-level functions.
- Format: Paperback
- ISBN: 9781638281542
- Publication Date: Feb 2023
- Availability: In Stock - Despatched Within 5 Working Days
A Journey through the History of Numerical Linear Algebra
Claude Brezinski
- Format: Hardback
- ISBN: 9781611977226
- Publication Date: Dec 2022
- Availability: In Stock - Despatched Within 5-7 Working Days
Solving Nonlinear Equations with Iterative Methods
C. T. Kelley
- Format: Paperback
- ISBN: 9781611977264
- Publication Date: Nov 2022
- Availability: In Stock - Despatched Within 5-7 Working Days
Matrix Analysis and Computations
Zhong-Zhi Bai
- Format: Paperback
- ISBN: 9781611976625
- Publication Date: Dec 2021
- Availability: In Stock - Despatched Within 5-7 Working Days
Discrete Mathematics with Cryptographic Applications
Alexander I. Kheyfits
- Format: Hardback
- ISBN: 9781683927631
- Publication Date: Oct 2021
- Availability: In Stock - Despatched Within 5-7 Working Days
Machine Learning Applications in Non-Conventional Machining Processes
Goutam Kumar Bose
- Format: Hardback
- ISBN: 9781799836247
- Publication Date: Feb 2021
- Availability: In Stock - Despatched Within 5 Working Days
Nonnegative Matrix Factorization
Nicolas Gillis
- Format: Paperback
- ISBN: 9781611976403
- Publication Date: Jan 2021
- Availability: In Stock - Despatched Within 5-7 Working Days
Computer Science, Algorithms and Complexity
Adele Kuzmiakova
- Format: Hardback
- ISBN: 9781774077481
- Publication Date: Dec 2020
- Availability: In Stock - Despatched Within 5-7 Working Days
Computer-Based Mathematics Education and the Use of MatCos Software in Primary and Secondary Schools
Francesco Aldo Costabile
- Format: Hardback
- ISBN: 9781799857181
- Publication Date: Aug 2020
- Availability: In Stock - Despatched Within 5 Working Days
MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities
Jiann-Ming Wu
Deep learning has become a trending area of research due to its adaptive characteristics and high levels of applicability. In recent years, researchers have begun applying deep learning strategies to image analysis and pattern recognition for solving technical issues within image classification. As these technologies continue to advance, professionals have begun translating this intelligent programming language into mobile applications for devices. Programmers and web developers are in need of significant research on how to successfully develop pattern recognition applications using intelligent programming. MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities is an essential reference source that presents a solution to developing intelligent pattern recognition Apps on iOS devices based on MatConvNet deep learning. Featuring research on topics such as medical image diagnosis, convolutional neural networks, and character classification, this book is ideally designed for programmers, developers, researchers, practitioners, engineers, academicians, students, scientists, and educators seeking coverage on the specific development of iOS mobile applications using pattern recognition strategies.
- Format: Hardback
- ISBN: 9781799815549
- Publication Date: Apr 2020
- Availability: In Stock - Despatched Within 5 Working Days
Interpolatory Methods for Model Reduction
Athanasios C. Antoulas
- Format: Paperback
- ISBN: 9781611976076
- Publication Date: Feb 2020
- Availability: In Stock - Despatched Within 5-7 Working Days
Handbook of Research on Emerging Trends and Applications of Machine Learning
Arun Solanki
As today's world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.
- Format: Hardback
- ISBN: 9781522596431
- Publication Date: Dec 2019
- Availability: In Stock - Despatched Within 5 Working Days