AI Basics for School Students (Mehrotra Dheeraj)
Dr. Dheeraj Mehrotra is an Academic
Evangelist, a former School Principal, with over 30 years of experience as an
academician with expertise in implementing TQM, Quality Circles, Six Sigma, 5S,
Kaizen, Experiential Learning and NLP (Neuro Linguistic Programming) in
Academics. As a National Teacher Awardee, year 2005, honored by the President
of India, he has published over 45 books, including a computer science series
for classes I – XII for CBSE/ CISCE curriculum and has trained over 8000
Teachers Globally on Classroom Management, NLP, Quality Management and Six
Sigma In Academics. He has been recently recognized by the LIMCA Book of
Records and INDIA book of Records for developing maximum number of Educational
Applications for the Google Play Store in India. He is a premium UDEMY
Instructor with over 200 Courses with an enrollment of over 4 Lacs covering 180
countries. He is also a TEDx speaker and a CBSE Master Trainer representing
Centre of Excellence, CBSE for varied teacher training programmes.
AI Basics for School Students (Mehrotra Dheeraj)
Language: English
Binding: Paperback
Publisher: University of Utah Press,U.S.
Pages: 70
AI - Artificial
Intelligence Basics For School Students (Class-IX)
(Dr Dheeraj
Mehrotra)
"AI Basics for
School Students" is not just a textbook but a launchpad for young minds to
explore the limitless possibilities of Artificial Intelligence. It equips them
with the knowledge, tools, and inspiration to become responsible and active
participants in shaping the future with AI.
"AI Basics for School Students" delves into the captivating world of Artificial Intelligence (AI), making it accessible and engaging for young minds. This book, crafted with clear explanations and fun examples, aims to spark curiosity and equip students with a foundational understanding of this rapidly evolving field.
The book begins by demystifying what AI truly is. It explains how AI mimics human intelligence by learning from data, recognizing patterns, and making decisions. The authors aptly use relatable comparisons, like self-driving cars and virtual assistants, to illustrate these concepts.
Moving beyond the definition, the book dives into the core tools that power AI. Students learn about machine learning, where algorithms "learn" from data, and deep learning, inspired by the structure of the brain. They encounter fascinating examples like facial recognition software and language translation apps, understanding how AI algorithms analyze and generate information.
The book then showcases the diverse applications of AI in our daily lives. From personalized recommendations on streaming platforms to medical diagnosis tools, students discover how AI is transforming various fields. Chapters dedicated to robotics, healthcare, and even space exploration showcase the possibilities and impact of AI on the future.
The book doesn't shy away from exploring the ethical considerations surrounding AI. Students learn about potential biases in algorithms, the importance of responsible data collection, and the need for human oversight. They are encouraged to think critically about the role of AI in society and its potential impact on various aspects of life.
To truly understand AI, the book encourages active participation. Through engaging activities and projects, students get a taste of coding, building basic AI programs, and experimenting with tools like chatbots and image recognition. This hands-on approach empowers them to become creators and innovators, not just passive consumers of technology.
"AI Basics for School Students" concludes by painting a picture of the future, where AI promises to reshape the world in exciting ways. Students are left with a sense of wonder and a desire to continue their exploration of this dynamic field. The book emphasizes the importance of developing critical thinking skills, creativity, and ethical awareness to navigate the ever-evolving landscape of AI.
AI - Artificial Intelligence Basics For School Students (Class-IX)
(Dr Dheeraj Mehrotra)
Language: English
Binding: Paperback
Publisher: Notion Press
Pages: 192
The Art of Prompt Engineering with ChatGPT
(Nathan
Hunter)
In the era of powerful language models like ChatGPT, "The Art of Prompt Engineering with ChatGPT" emerges as a crucial guide. It sheds light on the transformative art of crafting effective prompts, unlocking the full potential of this AI marvel. Whether you're a creative writer, an aspiring programmer, or simply curious about the world of AI, this book empowers you to go beyond basic interactions and delve into the heart of ChatGPT's capabilities.
The book opens by dispelling the mystery surrounding prompts. It introduces them as the instructions and information fed to ChatGPT, shaping its output and guiding its creative journey. Through engaging examples, the author illustrates how precise and well-structured prompts can lead to remarkable results, from generating captivating poems to crafting scripts for short films.
The journey deepens as the book delves into the key ingredients of a masterful prompt. We learn about setting context, establishing tone and emotion, providing relevant examples, and incorporating stylistic elements. We uncover the impact of different prompt formats, exploring open-ended prompts, fill-in-the-blanks templates, and even code-based constructs.
Equipped with the theoretical foundation, the book equips readers with practical tools to refine their prompt-crafting skills. We encounter techniques like chaining prompts together, utilizing keywords and modifiers, and employing specific triggers to evoke desired responses. Advanced tactics like fine-tuning and parameter adjustments unveil further layers of customization, allowing readers to truly personalize their interactions with ChatGPT.
Beyond the technical aspects, the book paints a vivid picture of the creative possibilities unlocked by expert prompt engineering. We embark on explorations through different artistic domains, discovering how prompts can fuel the generation of captivating stories, poems, scripts, and even song lyrics. The book ignites imagination, encouraging readers to experiment and unleash their own artistic potential through the lens of ChatGPT.
The Art of Prompt Engineering with ChatGPT
(Nathan
Hunter)
Binding: Paperback
Publisher: Shroff Hunter
Genre: Computing
& Information Technology
Pages: 152
All Indian Reprints of Nathan Hunter are
Printed in Grayscale. Unlock the full potential of chatGPT This easy-to-follow
book is the perfect resource for anyone looking to master the art of prompt
engineering and get the most out of the powerful AI tool. Written by a
technical and soft skills trainer, this book is filled with hands-on exercises
and practical tips to help you improve your skills. You’ll learn how to craft
the right requests to get the best results from chatGPT,and how to preserve
your own humanity while still getting the most out of the tool. Whether you’re
using chatGPT for writing, translation, or any other task, this book will help
you master the art of prompt engineering and achieve your goals.
Artifical Intelligence :
A Modern Approach
(Russell, Norvig)
Artificial Intelligence: A Modern Approach by Stuart Russell and Peter
Norvig is a comprehensive textbook that covers the fundamental concepts and
applications of artificial intelligence (AI). It is widely considered the
standard reference work in the field and is used as a textbook in many
universities around the world.
The book is divided into three parts :
Part 1: Foundations: This part provides an introduction to the basic
concepts of AI, such as problem solving, search, knowledge representation,
reasoning, and learning. It also covers some of the historical background of AI
and the different approaches that have been taken to the field.
Part 2: Problem Solving: This part focuses on specific problem-solving
methods, such as search algorithms, game playing, and constraint satisfaction.
It also discusses planning and scheduling, which are important for AI systems
that need to interact with the real world.
Part 3: Learning: This part covers the different ways that AI systems can
learn from data. It includes chapters on supervised learning, unsupervised
learning, reinforcement learning, and Bayesian learning.
Artificial Intelligence: A Modern Approach is an excellent resource for
anyone who wants to learn more about AI. It is a challenging but rewarding
read, and it is sure to give you a deep understanding of this fascinating
field.
Search algorithms: The book discusses a variety of search algorithms,
such as depth-first search, breadth-first search, and A* search. It also
discusses the complexity of search algorithms and how to choose the right
algorithm for a particular problem.
Game playing: The book discusses how AI can be used to play games, such
as chess and Go. It covers topics such as minimax search, alpha-beta pruning,
and Monte Carlo tree search.
Constraint satisfaction: The book discusses how AI can be used to solve
constraint satisfaction problems, such as scheduling and resource allocation.
It covers topics such as backtracking, forward checking, and arc consistency.
Planning and scheduling: The book discusses how AI can be used to plan
and schedule actions. It covers topics such as STRIPS planning, hierarchical
planning, and scheduling in dynamic environments.
Supervised learning: The book discusses how AI can be used to learn from labeled
data. It covers topics such as linear regression, decision trees, and support
vector machines.
Unsupervised learning: The book discusses how AI can be used to learn
from unlabeled data. It covers topics such as clustering, dimensionality
reduction, and anomaly detection.
Reinforcement learning: The book discusses how AI can learn from
experience through trial and error. It covers topics such as Q-learning, policy
gradient methods, and deep reinforcement learning.
Bayesian learning: The book discusses how AI can use Bayes' theorem to
make decisions under uncertainty. It covers topics such as Bayesian networks,
Markov chain Monte Carlo methods, and variational inference.
Artifical Intelligence : A Modern Approach
(Russell, Norvig)
Binding: Paperback
Publisher: Pearson
Pages: 1292
The long-anticipated revision of Artificial
Intelligence: A Modern Approach explores the full breadth and depth of the
field of artificial intelligence (AI). The 4th Edition brings readers up to
date on the latest technologies, presents concepts in a more unified manner,
and offers new or expanded coverage of machine learning, deep learning,
transfer learning, multiagent systems, robotics, natural language processing,
causality, probabilistic programming, privacy, fairness, and safe AI.
Table of Contents
1 Introduction
2 Intelligent Agents 3 Solving Problems by Searching 4 Search in Complex
Environments 5 Constraint Satisfaction Problems 6 Adversarial Search and Games
7 Logical Agents 8 First-Order Logic 9 Inference in First-Order Logic 10
Knowledge Representation 11 Automated Planning 12 Quantifying Uncertainty 13
Probabilistic Reasoning 14 Probabilistic Reasoning over Time 15 Making Simple
Decisions 16 Making Complex Decisions 17 Multiagent Decision Making 18 Learning
from Examples 19 Knowledge in Learning 20 Learning Probabilistic Models 21 Deep
Learning 22 Reinforcement Learning 23 Natural Language Processing 24 Deep
Learning for Natural Language Processing 25 Robotics 26 Computer Vision 27
Philosophy and Ethics of AI 28 Future of AI 29 Probabilistic Programming
(Online)
