This book covers the psychology of teaching and learning and focuses on applying up-to-date as well as traditional theory in the classroom. It covers a range of issues that most concern the new teacher, written clearly and at an appropriate level.

This book discusses Artificial Neural Networks (ANN) and their ability to predict outcomes using deep and shallow learning principles. The author first describes ANN implementation, consisting of at least three layers that must be established together with cells, one of which is input, the other is output, and the third is a hidden (intermediate) layer. For this, the author states, it is necessary to develop an architecture that will not model mathematical rules but only the action and response variables that control the event and the reactions that may occur within it. The book explains the reasons and necessity of each ANN model, considering the similarity to the previous methods and the philosophical - logical rules.

TAGLINE Empower Your Data Insights with Java's Top Tools and Frameworks. KEY FEATURES ● Explore diverse techniques and algorithms for data analytics using Java. ● Learn through hands-on examples and practical applications in each chapter. ● Master essential tools and frameworks such as JFreeChart for data visualization and Deeplearning4j for deep learning. DESCRIPTION This book is a comprehensive guide to data analysis using Java. It starts with the fundamentals, covering the purpose of data analysis, different data types and structures, and how to pre-process datasets. It then introduces popular Java libraries like WEKA and Rapidminer for efficient data analysis. The middle section of the book dives deeper into statistical techniques like descriptive analysis and random sampling, along with practical skills in working with relational databases (JDBC, SQL, MySQL) and NoSQL databases. It also explores various analysis methods like regression, classification, and clustering, along with applications in business intelligence and time series prediction. The final part of the book gives a brief overview of big data analysis with Java frameworks like MapReduce, and introduces deep learning with the Deeplearning4J library. Whether you're new to data analysis or want to improve your Java skills, this book offers a step-by-step approach with real-world examples to help you master data analysis using Java. WHAT WILL YOU LEARN ● Understand foundational principles and types of data analytics, including descriptive, diagnostic, predictive, and prescriptive analytics. ● Master techniques for preprocessing data, including cleaning and munging, to prepare it for analysis. ● Learn how to create various charts and plots including bar charts, histograms, and scatter plots for effective data visualization. ● Explore Java-based libraries such as WEKA and Deeplearning4j for implementing machine learning algorithms. ● Develop expertise in statistical techniques including hypothesis testing, regression (linear and polynomial), and probability distributions. ● Acquire practical skills in SQL querying and JDBC for relational databases. ● Explore applications in business intelligence and deep learning, including image recognition and natural language processing. WHO IS THIS BOOK FOR? This book is ideal for IT professionals, software developers, and data scientists interested in using Java for data analytics. It is also suitable for students and researchers seeking practical insights into Java-based data analysis. Readers should have a basic understanding of Java programming and fundamental concepts in data analysis. TABLE OF CONTENTS 1. Data Analytics Using Java 2. Datasets 3. Data Visualization 4. Java Machine Learning Libraries 5. Statistical Analysis 6. Relational Databases 7. Regression Analysis 8. Classification Analysis 9. Sentiment Analysis 10. Cluster Analysis 11. Working with NoSQL Databases 12. Recommender Systems 13. Applications of Data Analysis 14. Big Data Analysis with Java 15. Deep Learning with Java Index

As the advancement of technology continues, cyber security continues to play a significant role in today’s world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.

This is an open access book. As a leading role in the global megatrend of scientific innovation, China has been creating a more and more open environment for scientific innovation, increasing the depth and breadth of academic cooperation, and building a community of innovation that benefits all. These endeavors have made new contribution to globalization and creating a community of shared future. 2022 International Conference on Educational Innovation and Multimedia Technology (EIMT 2022) was held on March 25-27, 2022 in Hangzhou, China (Due to the epidemic, the meeting was moved to online). The aim of the conference is to bring together innovative academics and industrial experts in the field of Educational Innovation and Multimedia Technology to a common forum. The primary goal of the conference is to promote research and developmental activities in the related field.

Learning to teach involves hard work and careful preparation. To become an effective teacher requires subject knowledge, an understanding of your pupils and the confidence to respond to dynamic classroom situations. This best-selling textbook offers a sound and practical introduction to the skills needed to gain Qualified Teacher Status, and will help you to develop those qualities that lead to good practice and a successful future in education. This 4th edition has been updated to include changes to the National Curriculum for England and Wales, as well as changes to the organization of, and curriculum for, early professional development. With a focus on evidence-based practice, the book is packed with examples of how to analyze practice to ensure pupil learning is maximized. Activities in each chapter also provide an analytical toolkit to help you to analyze your own learning and performance. Web-based links to sources of new knowledge that support evidence-based practice are also included. Witheven more useful strategies and ideas, Learning to Teach in the Secondary School,4th edition covers the range of situations and potential problems faced by the student teacher and the newly qualified teacher. The book contains 29 units, organized into 9 chapters, each covering a key concept or skill, including: Managing classroom behavior Understanding the ways pupils learn Planning lessons and schemes of work Differentiation, progression and pupil grouping Assessment and recording Inclusion and special educational needs using ICT in teaching and learning Understanding schools in society Getting your first teaching post

As new technologies and professional profiles emerge, traditional education paradigms have to be adapted to new scenarios, creating favorable conditions for promoting transversal skills among students. Consequently, there is a growing demand for training in emergent skills to solve problems of different natures, distributive leadership competencies, empathy, ability to control emotions, etc. In this sense, one of the challenges that educators of all different educational levels and training contexts have to face is to foster these skills in their courses. To overcome these obstacles, innovative and disruptive methodologies, such as game-based learning activities like escape rooms, can be a great ally for teachers to work on transversal skills and specific knowledge at the same time. The Handbook of Research on Using Disruptive Methodologies and Game-Based Learning to Foster Transversal Skills gathers knowledge, skills, abilities, and capabilities on innovative and disruptive methodologies that can be applied in all educational levels to foster transversal skills. This publication contains different contributions focused on the description of innovative educational methods, processes, and tools that can be adopted by teachers to promote transversal skills such as creativity, critical thinking, decision-making, and entrepreneurial skills. This book is ideal for teachers, instructional designers, educational software developers, academics, professionals, students, and researchers working at all levels in the educational field and provides valuable background information to professionals who aim to overcome traditional paradigm obstacles and meet student needs by means of innovative and disruptive methodologies.

This book explains how various forms of artificial intelligence, namely machine learning, natural language processing, and robotic process automation, could provide a source of competitive advantage to firms deploying them compared to those firms that would not have deployed these technologies. The advantages of machine learning, natural language processing, and robotic process automation in strategy formulation and strategy implementation are explored. The book illustrates the potential sources of advantage for the strategy formulation and strategy implementation processes, which can be derived from the deployment of each form of artificial intelligence.

Gain a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform. Most of the major AI topics will be explored, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more! AI in action will be demonstrated using the Python language on the Raspberry Pi. The Prolog language will also be introduced and used to demonstrate fundamental AI concepts. In addition, the Wolfram language will be used as part of the deep machine learning demonstrations. A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. Minimal expense is needed for the projects as only a few sensors and actuators will be required. Beginners and hobbyists can jump right in to creating AI projects with the Raspberry PI using this book. What You'll Learn What AI is and—as importantly—what it is not Inference and expert systems Machine learning both shallow and deep Fuzzy logic and how to apply to an actual control system When AI might be appropriate to include in a system Constraints and limitations of the Raspberry Pi AI implementation Who This Book Is For Hobbyists, makers, engineers involved in designing autonomous systems and wanting to gain an education in fundamental AI concepts, and non-technical readers who want to understand what AI is and how it might affect their lives.