This book constitutes the proceedings of the 4th International Conference on Advances in Emerging Trends and Technologies (ICAETT 2022), held in Riobamba, Ecuador, on 26–28 October 2022, proudly organized by Facultad de Informática y Electrónica (FIE) at Escuela Superior Politécnica de Chimborazo and supported by GDEON. ICAETT 2022 brings together top researchers and practitioners working in different domains of computer science to share their expertise and to discuss future developments and potential collaborations. Presenting high-quality, peer-reviewed papers, the book discusses the following topics: ● Artificial intelligence ● Communications ● e-Learning ● AT for engineering applications ● Security ● Technology trends
This book provides glimpses into contemporary research in information systems & technology, learning, artificial intelligence (AI), machine learning, and security and how it applies to the real world, but the ideas presented also span the domains of telehealth, computer vision, the role and use of mobile devices, brain–computer interfaces, virtual reality, language and image processing and big data analytics and applications. Great research arises from asking pertinent research questions. This book reveals some of the authors’ “beautiful questions” and how they develop the subsequent “what if” and “how” questions, offering readers food for thought and whetting their appetite for further research by the same authors.
Embark on an illuminating journey into the realm of "MACHINE LEARNING" with our definitive MCQ guide, "LearnML." Tailored for enthusiasts, students, and professionals venturing into the dynamic field of machine learning, this resource is your key to unraveling the intricacies of algorithms, models, and the transformative potential of machine learning technologies. Dive into a knowledge-rich experience, progressing from foundational to advanced concepts through a series of thoughtfully curated multiple-choice questions. Key Features: MCQ Exploration: Navigate through a diverse array of questions covering fundamental principles, machine learning algorithms, and the unique characteristics of model training, ensuring a comprehensive understanding of this transformative field. Detailed Explanations: Elevate your knowledge with comprehensive explanations accompanying each MCQ, unraveling the intricacies of supervised learning, unsupervised learning, and the principles that define the power of machine learning. Real-World Applications: Bridge theory and practice, connecting machine learning concepts to real-world applications in predictive analytics, recommendation systems, and the dynamic landscape of AI-driven solutions. Progressive Difficulty Levels: Challenge yourself with questions ranging from foundational to advanced, providing a structured learning experience suitable for learners at all levels. Visual Learning Tools: Reinforce your understanding with visual aids such as machine learning flowcharts, algorithmic diagrams, and examples of machine learning applications, enhancing your grasp of machine learning concepts. Embark on a quest for machine learning mastery with "LearnML: MACHINE LEARNING." Download your copy now to master the essential skills needed for understanding the transformative potential of machine learning. Whether you're a student, machine learning enthusiast, or a professional in the field, this guide is your key to unlocking the capabilities of machine learning with precision and expertise.
This book focuses on the use of Artificial Intelligence and Machine Learning (AI/ML) based techniques to solve issues related to communication networks, their layers, as well as their applications. The book first offers an introduction to recent trends regarding communication networks. The authors then provide an overview of theoretical concepts of AI/ML, techniques and protocols used in different layers of communication. Furthermore, this book presents solutions that help analyze complex patterns in user data and ultimately improve productivity. Throughout, AI/ML-based solutions are provided, for topics such as signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction, software-defined networking, congestion control, communication network optimization, security, and anomaly detection. The book features chapters from a large spectrum of authors including researchers, students, as well as industrials involved in research and development.
Learn how to harness the power of ChatGPT to streamline data analysis, accelerate model development, and unlock innovative solutions to real-world problems. KEY FEATURES ● Step-by-step progression from foundational machine learning concepts to advanced techniques using ChatGPT and Google Colab. ● Clear and detailed instructions for data preparation, model training, and evaluation, simplifying complex machine learning tasks. ● Extensive use of Google Colab for coding and experimentation, providing a real-world platform to apply learned techniques effectively. DESCRIPTION Unlock the future of machine learning by mastering Google Colab, trusted by over 5 million data scientists, and ChatGPT, powering 100 million users worldwide. This book bridges the latest in AI with practical, hands-on applications for data science. With these game-changing tools at your command, you’ll be able to streamline complex workflows, automate tedious tasks, and propel your AI skills to new heights—making machine learning faster, smarter, and more accessible than ever before. Each chapter unfolds a specific aspect of data science and machine learning, seamlessly integrated with ChatGPT’s free version capabilities. The foundational chapters introduce key machine learning concepts, while advanced sections explore topics such as natural language processing, sentiment analysis, and predictive analytics—all illustrated with real-world examples and interactive exercises. The later chapters focus on optimizing tasks using the more powerful paid version of ChatGPT, culminating in the creation of a custom GPT named “Data Scientist” to tackle specialized challenges. Additionally, the book includes a section on best practices, expert tips, and interview questions, making it a comprehensive resource for aspiring data scientists and seasoned professionals alike. WHAT WILL YOU LEARN ● Learn to integrate and optimize ChatGPT and Google Colab for enhanced data science tasks. ● Master techniques for preparing and cleaning data for analysis. ● Gain a solid grasp of statistical concepts essential for data science. ● Learn the processes for training, evaluating, and refining machine learning models. ● Perform data analysis and preprocessing using natural language processing techniques. ● Customize and deploy GPT models for specific data science applications. WHO IS THIS BOOK FOR? This book is ideal for aspiring data scientists and machine learning enthusiasts eager to enhance their skills with ChatGPT and Google Colab. It also serves tech professionals, academics, and business analysts seeking practical insights into AI and data science. A basic understanding of programming, statistics, and data analysis is recommended before diving in. TABLE OF CONTENTS 1. Introduction to ChatGPT 2. ChatGPT for Data Science and Machine Learning 3. Fundamentals of Statistics for Data Science 4. Missing Values and Outliers 5. Relation Between Variables and Charts 6. Data Preparation 7. Training and Evaluation 8. Fine Tuning, Features Selection, and Final Model 9. Data Preparation and Training 10. Fine Tuning and Final Model 11. Data Analysis and Dataset Manipulation (NLP) 12. Sentiment Analysis and Predictions 13. ChatGPT-4 for a Completely Automated Data Science Workload 14. Customizing GPT for Applications 15. Takeaways and Conclusions Index
The rise of internet and social media usage in the past couple of decades has presented a very useful tool for many different industries and fields to utilize. With much of the world’s population writing their opinions on various products and services in public online forums, industries can collect this data through various computational tools and methods. These tools and methods, however, are still being perfected in both collection and implementation. Sentiment analysis can be used for many different industries and for many different purposes, which could better business performance and even society. The Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines discusses the tools, methodologies, applications, and implementation of sentiment analysis across various disciplines and industries such as the pharmaceutical industry, government, and the tourism industry. It further presents emerging technologies and developments within the field of sentiment analysis and opinion mining. Covering topics such as electronic word of mouth (eWOM), public security, and user similarity, this major reference work is a comprehensive resource for computer scientists, IT professionals, AI scientists, business leaders and managers, marketers, advertising agencies, public administrators, government officials, university administrators, libraries, students and faculty of higher education, researchers, and academicians.
This multidisciplinary, international Research Handbook on Inequalities and Work examines disparities within contemporary working life and comes at a critical juncture of socio-historical change. As the world reels from the impact of economic insecurity, the pandemic, the Black Lives Matter and #MeToo movements, the trans liberation fight, the climate crisis and the rise of Artificial Intelligence, systemic inequalities and their impacts have been thrust into the limelight alongside the ceaseless struggle for social justice. Against this background, the Handbook provides cutting edge research studies that offers unique insight into the international nature of inequalities at work.
This book constitutes the proceedings of the 6th International Conference on Decision Support Systems Technologies, ICDSST 2020, organised in Zaragoza, Spain, in May 2020. The conference was held online only due to the Corona pandemic. The EWG-DSS series of International Conference on Decision Support System Technology (ICDSST) is planned to consolidate the tradition of annual events organized by the EWG-DSS in offering a platform for European and international DSS communities, comprising the academic and industrial sectors, to present state-of-the-art DSS research and developments, to discuss current challenges that surround decision-making processes, to exchange ideas about realistic and innovative solutions, and to co-develop potential business opportunities. The main topic of this year’s conference was “Cognitive Decision Support Systems and Technologies”. The 13 papers presented in this volume were carefully reviewed and selected from 51 submissions. They were organized in topical sections named: methodological contributions; case studies and applications; and overview (on the current state and future trends of DSS, BI, and data analytics research).
Onlearning - How disruptive education reinvents learning brings a new concept, which appears as a response to the desire for change in education, specifically in education for executives, in the face of the exponential and out-of-sync transformations of society, which happen through technology and revolutionize organizations, people's lives and customs; with the aim of extracting the best from this evolution and expanding it in a maximized way into executive learning. The work consists of three parts: Part I deals with the history of work–oriented education, executive education, and business schools. It shows how the teaching of Administration was formalized, mainly by business schools, and what learning and cognition methodologies were developed by the various thinkers of the 19th and 20th centuries, whose models have repercussions until today. Part II outlines the scenario in which technology and digital transformation are consolidated as fundamental means for creating disruption in the most diverse areas of knowledge and industry sectors. It approaches how Clayton Christensen's theory of disruptive strategy defies the logic of traditional innovation, as well as what are the effects of new technologies on the economy, society and people's lives, and how fast are they advancing to become accessible, radically transforming reality. Finally, Part III deals with education and Saint Paul's disruptive proposal for executive education, Onlearning. It reflects on the need for education to concretely impact technological evolution in a broad way, in its economic and social aspect. It ends by presenting 20 conclusions on Onlearning, featuring objectives, actions, and projections for the future of education, based on the proposal to reinvent education through the resources that technology and digital transformation make available to everyone.
This book is related to the educational networking (EN) domain, an incipient but disrupting trend engaged in extending and improving formal and informal academic practices by means of the support given by online social networks (OSNs) and Web 2.0 technologies. With the aim of contributing to spread the knowledge and development of the arena, this volume introduces ten recent works, whose content meets the quality criteria of formal scientific labor that is worthy to be published according to following five categories: · Reviews: gather three overviews that focus on K-12 EN practice, mixed methods approaches using social network analysis for learning and education, and a broad landscape of the recent accomplished labor. · Conceptual: presents a work where a theoretical framework is proposed to overcome barriers that constrain the use of OSNs for educational purposes by means of a Platform Adoption Model. · Projects: inform a couple of initiatives, where one fosters groups and networks for teachers involved in distance education, and the other encourages students the author academic videos to improve motivation and engagement. · Approaches: offer three experiences related to: Wiki and Blog usage for assessment affairs, application of a method that encourages OSNs users to actively post and repost valuable information for the learning community, and the recreation of learning spaces in context–aware to boost EN. · Study: applies an own method to ranking Mexican universities based on maximal clique, giving as a result a series of complex visual networks that characterize the tides among diverse features that describe academic institutions practice. In resume, this volume offers a fresh reference of an emergent field that contributes to spreading and enhancing the provision of education in classrooms and online settings through social constructivism and collaboration policy. Thus, it is expected the published content encourages researchers, practitioners, professors, and postgraduate students to consider their future contribution to extent the scope and impact of EN in formal and informal teaching and learning endeavors.
