Hands-On Artificial Intelligence with TensorFlow

Python

Beginner's Guide to Artificial Intelligence

Denis Rothman, Matthew Lamons, Rahul Kumar

Develop real-world applications powered by the latest advances in intelligent systems Key Features Gain real-world contextualization using deep learning problems concerning research and application Get to know the best practices to improve and optimize your machine learning systems and algorithms Design and implement machine intelligence using real-world AI-based examples Book Description This Learning Path offers practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. You will be introduced to various machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. You will learn to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open-source Python libraries. Throughout the Learning Path, you'll learn how to develop deep learning applications for machine learning systems. Discover how to attain deep learning programming on GPU in a distributed way. By the end of this Learning Path, you know the fundamentals of AI and have worked through a number of case studies that will help you apply your skills to real-world projects. This Learning Path includes content from the following Packt products: Artificial Intelligence By Example by Denis Rothman Python Deep Learning Projects by Matthew Lamons, Rahul Kumar, and Abhishek Nagaraja Hands-On Artificial Intelligence with TensorFlow by Amir Ziai, Ankit Dixit What you will learn Use adaptive thinking to solve real-life AI case studies Rise beyond being a modern-day factory code worker Understand future AI solutions and adapt quickly to them Master deep neural network implementation using TensorFlow Predict continuous target outcomes using regression analysis Dive deep into textual and social media data using sentiment analysis Who this book is for This Learning Path is for anyone who wants to understand the fundamentals of Artificial Intelligence and implement it practically by devising smart solutions. You will learn to extend your machine learning and deep learning knowledge by creating practical AI smart solutions. Prior experience with Python and statistical knowledge is essential to make the most out of this Learning Path.

텐서플로우로 구현한 인공지능 실습

Amir Ziai

Description unavailable for this volume in the current provider response.

Guide To Artificial Intelligence

Hemant Vilas Deshmukh

This book provides a clear and comprehensive introduction to Artificial Intelligence and its growing impact across industries such as healthcare, finance, education, transportation, and cybersecurity. With the increasing importance of AI in modern technology, the author recognized the need for a resource that explains AI concepts in simple, easy-to-understand English for students, IT professionals, and general readers. The book covers essential topics including the fundamentals of Artificial Intelligence, types of AI, machine learning, deep learning, neural networks, data analytics and visualization, natural language processing, computer vision, and the role of AI in robotics. It also explores the applications of AI in cybercrime and cybersecurity. Designed with reference to academic curricula and industry needs, this book aims to provide practical knowledge and foundational understanding, making it a useful guide for learners and professionals interested in Artificial Intelligence.

Artificial Intelligence

Latest Advances, New Paradigms and Novel Applications

Unknown author

Artificial Intelligence (AI) is widely known as a knowledge field that aims to make computers, robots, or products that mimic the way humans think. In the current scientific community, AI is an intensively studied area composed of multiple branches. Historically, machine learning and optimization are two of the most studied fronts thanks to the development of novel and challenging research topics such as transfer optimization, swarm robotics, and drift detection and adaptation to evolving conditions in real-time. This book collects radically new theoretical insights, reporting recent developments and evincing innovative applications regarding AI methods in all fields of knowledge. It also presents works focused on new paradigms and novel branches of AI science.

Artificial Intelligence for Future Society

Proceedings of the International Conference on Artificial Intelligence for Society

Vasile Palade, Margarita Favorskaya, Srikanta Patnaik, Milan Simic, Smaranda Belciug

"Artificial Intelligence for Future Society" presents the revolution in future societies by enhancing efficiency, connectivity, and personalization across various sectors. Its future aspects include the integration of AI in everyday life through smart cities, autonomous vehicles, and advanced healthcare systems, providing a more intelligent, responsive, and adaptive environment that meets the evolving needs of humanity. This volume explores the most recent innovations and significant developments in the domains of Artificial Intelligence and its impact in transforming society, propelling innovation across diverse fields such as healthcare, education, finance, and transportation. It spans a wide range of dimensions, including: Societal Diversity Innovation in the Digital Age Business Information Systems Advancement in Healthcare, HSI, and Global Collaboration By merging cutting-edge theoretical insights with practical applications, this volume provides researchers, practitioners, and students with the essential knowledge and tools to explore and advance within the dynamic field of Artificial Intelligence. Artificial Intelligence brings numerous benefits to society, including improved efficiency and productivity in various industries through automation and intelligent data analysis. It enhances healthcare with advanced diagnostic tools and personalized treatment plans, and provides smarter living environments through smart cities and innovative technologies.

Innovations in Artificial Intelligence and Human-Computer Interaction in the Digital Era

Surbhi Bhatia Khan, Suyel Namasudra, Swati Chandna, Arwa Mashat

Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches. Chapters explore how well AI can interact with users based on linguistics and user-centered design processes, especially with the advances of AI and the hype around many applications. Other sections investigate how HCI and AI can mutually benefit from a closer association and the how the AI community can improve their usage of HCI methods like "Wizard of Oz prototyping and "Thinking aloud protocols. Moreover, HCI can further augment human capabilities using new technologies. This book demonstrates how an interdisciplinary team of HCI and AI researchers can develop extraordinary applications, such as improved education systems, smart homes, smart healthcare and map Human Computer Interaction (HCI) for a multidisciplinary field that focuses on the design of computer technology and the interaction between users and computers in different domains. - Presents fundamental concepts of both HCI and AI, addressing a multidisciplinary audience of researchers and engineers working on User Centered Design (UCD), User Interface (UI) design, and User Experience (UX) design - Explores a broad range of case studies from across healthcare, industry, and education - Investigates multiple strategies for designing and developing intelligent user interfaces to solve real-world problems - Outlines research challenges and future directions for the intersection of AI and HCI

Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments

Gupta, Manisha, Sharma, Deergha, Gupta, Himani

Throughout the world, artificial intelligence is reshaping businesses, trade interfaces, economic activities, and society as a whole. In recent years, scholarly research on artificial intelligence has emerged from a variety of empirical and applied domains of knowledge. Computer scientists have developed advanced deep learning algorithms to leverage its utility in a variety of fields such as medicine, energy, travel, education, banking, and business management. Although a growing body of literature is shedding light on artificial intelligence-enabled difficulties, there is still much to be gained by applying fresh theory-driven techniques to this vital topic. Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments provides a comprehensive understanding of the business systems, platforms, procedures, and mechanisms that underpin different stakeholders' experiences with reality-enhancing technologies and their transformative application in management. The book also identifies areas in various business processes where artificial intelligence intervention would not only transform the business but would also make the business more sustainable. Covering key topics such as blockchain, business automation, and manufacturing, this reference work is ideal for computer scientists, business owners, managers, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Computer Science and Education. AI Shaping Education

19th International Conference, ICCSE 2025, Osaka & Fukui, Japan, August 19–24, 2025, Proceedings, Part II

Wenxing Hong, Binyue Cui, Yang Weng, Chao Li

This two-volume set constitutes the proceedings of the 19th International Conference on Computer Science and Education, ICCSE 2025, held in Osaka & Fukui, Japan, during August 19–24, 2025. The 82 full papers and 2 short papers presented were thoroughly reviewed and selected from the 196 submissions. They were focused on the following topical sections: Part I : AI Technology Frontiers-Computer Science and Data Science; Artificial Intelligence and Machine Learning and Natural Language Processing and Text Analytics Part II : AI Shaping Education-AI Applications in Education and Teaching Models and Educational Reform.