Overview

""AI in Communication and Technologies"" is a comprehensive, practical-oriented textbook designed to serve as a definitive guide for undergraduate (B.Tech) and postgraduate (M.Tech) students of Computer Science and allied engineering disciplines. It meticulously bridges the gap between the theoretical underpinnings of Artificial Intelligence and its real-world application in modern communication systems. The book is engineered to be a primary resource for students, educators, and self-learners aiming to master the skills needed to design, develop, and deploy AI-powered communication solutions. Philosophy The core philosophy of this book is ""learning by doing."" It is built on the pedagogical belief that deep and lasting knowledge in an engineering discipline is acquired through hands-on application, not passive observation. I deliberately shift the focus from rote memorization of complex mathematical theories to the intuitive understanding and practical implementation of algorithms and systems. Every concept is introduced with the ultimate goal of answering the question: ""How can I build this?"" Key Features 1. Strictly Practical Orientation: Over 70% of the book is dedicated to implementation details, code examples, hands-on tutorials, and case studies. The primary goal is to empower readers to build working applications. 2. Step-by-Step Implementation: The book provides clear, sequential guidance on how to develop solutions. From setting up the development environment to deploying a finished application, every step is explained. 3. Simplified Algorithms: Algorithms for concepts like machine learning models or network optimization are presented in a simple, pseudocode-like format using numbered lists, making them accessible even to those with a limited mathematical background. 4. End-to-End Project-Based Learning: The final chapter features a complete DIY capstone project that integrates concepts from across the book. It includes the problem statement, system design, complete working code with line-by-line explanations, and deployment instructions. 5. Industry-Relevant Technologies: The examples and projects utilize modern frameworks, libraries, and platforms (such as Python, TensorFlow/PyTorch, Scikit-learn, NLTK, etc.) that are prevalent in the industry. 6. Real-Life Examples and Case Studies: Concepts are illustrated with relatable, real-world examples, such as AI in 5G/6G networks, smart assistants, video conferencing, and IoT communication, to enhance understanding and engagement. Key Takeaways Upon completing this book, the reader will be able to: 1. Understand the Fundamentals: Grasp the core concepts of AI and its specific relevance to communication technologies. 2. Design AI-Powered Systems: Architect and design intelligent communication systems, from chatbots to smart network controllers. 3. Implement Practical Solutions: Write code to implement machine learning models for tasks like natural language understanding, speech recognition, and network optimization. 4. Develop and Deploy Applications: Build, test, and understand the deployment process for real-world AI communication applications. 5. Analyze and Solve Problems: Apply AI techniques to solve complex challenges in modern communication, such as ensuring Quality of Service (QoS), enhancing security, and managing network resources efficiently. 6. Build a Complete Project: Successfully complete a significant capstone project, demonstrating a comprehensive ability to apply the book's teachings from conception to execution. Disclaimer: Earnest request from the Author. Kindly go through the table of contents and refer kindle edition for a glance on the related contents. Thank you for your kind consideration!

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