A Textbook Of Artificial Intelligence For Class 10

Goyal Brothers Prakashan

Since its publication, Essentials of Artificial Intelligence has been adopted at numerous universities and colleges offering introductory AI courses at the graduate and undergraduate levels. Based on the author's course at Stanford University, the book is an integrated, cohesive introduction to the field. The author has a fresh, entertaining writing style that combines clear presentations with humor and AI anecdotes. At the same time, as an active AI researcher, he presents the material authoritatively and with insight that reflects a contemporary, first hand understanding of the field. Pedagogically designed, this book offers a range of exercises and examples.

This textbook covers the broader field of artificial intelligence. The chapters for this textbook span within three categories: Deductive reasoning methods: These methods start with pre-defined hypotheses and reason with them in order to arrive at logically sound conclusions. The underlying methods include search and logic-based methods. These methods are discussed in Chapters 1through 5. Inductive Learning Methods: These methods start with examples and use statistical methods in order to arrive at hypotheses. Examples include regression modeling, support vector machines, neural networks, reinforcement learning, unsupervised learning, and probabilistic graphical models. These methods are discussed in Chapters~6 through 11. Integrating Reasoning and Learning: Chapters~11 and 12 discuss techniques for integrating reasoning and learning. Examples include the use of knowledge graphs and neuro-symbolic artificial intelligence. The primary audience for this textbook are professors and advanced-level students in computer science. It is also possible to use this textbook for the mathematics requirements for an undergraduate data science course. Professionals working in this related field many also find this textbook useful as a reference.

A Textbook of Artificial Intelligence for Class 9

Artificial Intelligence: A Modern Approach offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.

The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.

Artificial Intelligence (AI) is being widely recognized to be the power that will fuel the future global digital economy. AI in the past few years has gained geostrategic importance and a large number of countries are striving hard to stay ahead with their policy initiatives to get their country already. AI is a continually advancing and expanding field and AI readiness will lead to better opportunities and increased levels of understanding. It will help them visualize jobs of the future and prepare for them. Its multidisciplinary nature will help to make connections between all other subjects thereby adding value and giving a different perspective for all. The CBSE curriculum focuses on building AI readiness in young minds. The importance of skill-based education and the value of project-related work is clear in order to "effectively harness the potential of AI in a sustainable manner to make India's next-generation 'AI ready'. AB a beginning in this direction, CBSE introduced Artificial Intelligence starting from Class VI onward. Students should opt for this curriculum to become future-ready and become at par with their counterparts at a global level. The aim is to strive together to make our students future-ready and help they work on incorporating Artificial Intelligence to improve their learning experience. Goyal Brothers Prakashan

The book featuring “AI BASICS FOR SCHOOL STUDENTS” targets learning of concepts as prescribed by the CBSE. The objective of the module is to develop a readiness for understanding and appreciating Artificial Intelligence and its application in our lives. The units dwelled include Excite, Relate, Purpose, Possibilities and AI Ethics which are set to empower the kids to identify and appreciate AI and describe its applications in daily life and to apply and reflect on the Human-Machine Interactions.