AI and Intelligent Computing (Paperback)
Idioma: inglés
Editorial: Independently Published, 2026
- Tapa blanda
- Nuevo
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Vendedor de IberLibro desde 12 de octubre de 2005
Condición: Nuevo
EUR 35,13
Cantidad disponible: 1 disponible
Añadir al carritoDescripción del artículo del vendedor
Paperback. "AI and Intelligent Computing" is a comprehensive, strictly practical, and industry-oriented manual designed to teach artificial intelligence and intelligent software development from the ground up. It is meticulously structured to guide the reader from absolute scratch-beginning with fundamental concepts and basic system setups-all the way through to the design, build, deployment, and implementation of live, production-ready applications. Philosophy The core philosophy of this book is rooted in practical implementation and demystification. For too long, the field of intelligent computing has been guarded by heavy theoretical jargon and abstract mathematics. This book operates on the belief that artificial intelligence is fundamentally a software engineering discipline. The philosophy here is "build first, refine later." I believe that learners grasp complex concepts most effectively when they can see them working in real-time. Therefore, the emphasis is heavily skewed toward practical applications and their implementations rather than theoretical proofs. Key Features This book is packed with features designed to bridge the gap between learning and doing: 1. Scratch to Production Pipeline: Uniquely covers the entire lifecycle of an intelligent application, including architecture design, model building, environment setup, deployment, and final production. 2. Industry-Relevant Tools: Focuses exclusively on the latest, updated frameworks, components, and cloud services currently demanded by the real-life tech industry. 3. Hands-on Practicals and Case Studies: Every chapter (where applicable) contains practical implementations, real-world case studies, and functioning code snippets. 4. Comprehensive Chapter Architecture: Every topic strictly details the design, model, framework, services, components, functioning, mode of operations, and future scope. 5. Step-by-Step Capstone Project: The final chapter is a complete Do-It-Yourself (DIY) working project, integrating all previous chapters into a single, deployable live application with line-by-line explanations. Key Takeaways By the time you complete this book, you will walk away with a highly valuable, highly marketable skill set. You will be able to: 1. Understand the complete history, evolution, classification, and industry necessity of intelligent computing systems. 2. Set up robust, scalable development environments from scratch. 3. Read, understand, and write algorithms using simplified, logical, step-by-step sequences. 4. Design the architecture for intelligent applications, selecting the appropriate models, frameworks, and components. 5. Implement machine learning and deep learning models to solve specific, real-life practical problems. 6. Execute data engineering, natural language processing, and computer vision tasks using industry-standard libraries. 7. Evaluate, tune, and optimize intelligent models for peak performance. 8. Deploy applications seamlessly into production environments using modern MLOps, containerization, and cloud services. 9. Fully develop and implement a live, working DIY capstone project from scratch to the final production stage. 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! This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
N° de ref. del artículo 9798185108581
- Título
- AI and Intelligent Computing (Paperback)
- Autor
- Ajit Singh
- Editorial
- Independently Published
- Año de publicación
- 2026
- Estado
- new
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 13
- 9798185108581
Philosophy
The core philosophy of this book is rooted in practical implementation and demystification. For too long, the field of intelligent computing has been guarded by heavy theoretical jargon and abstract mathematics. This book operates on the belief that artificial intelligence is fundamentally a software engineering discipline. The philosophy here is "build first, refine later." I believe that learners grasp complex concepts most effectively when they can see them working in real-time. Therefore, the emphasis is heavily skewed toward practical applications and their implementations rather than theoretical proofs.
Key Features
This book is packed with features designed to bridge the gap between learning and doing:
1. Scratch to Production Pipeline: Uniquely covers the entire lifecycle of an intelligent application, including architecture design, model building, environment setup, deployment, and final production.
2. Industry-Relevant Tools: Focuses exclusively on the latest, updated frameworks, components, and cloud services currently demanded by the real-life tech industry.
3. Hands-on Practicals and Case Studies: Every chapter (where applicable) contains practical implementations, real-world case studies, and functioning code snippets.
4. Comprehensive Chapter Architecture: Every topic strictly details the design, model, framework, services, components, functioning, mode of operations, and future scope.
5. Step-by-Step Capstone Project: The final chapter is a complete Do-It-Yourself (DIY) working project, integrating all previous chapters into a single, deployable live application with line-by-line explanations.
Key Takeaways
By the time you complete this book, you will walk away with a highly valuable, highly marketable skill set. You will be able to:
1. Understand the complete history, evolution, classification, and industry necessity of intelligent computing systems.
2. Set up robust, scalable development environments from scratch.
3. Read, understand, and write algorithms using simplified, logical, step-by-step sequences.
4. Design the architecture for intelligent applications, selecting the appropriate models, frameworks, and components.
5. Implement machine learning and deep learning models to solve specific, real-life practical problems.
6. Execute data engineering, natural language processing, and computer vision tasks using industry-standard libraries.
7. Evaluate, tune, and optimize intelligent models for peak performance.
8. Deploy applications seamlessly into production environments using modern MLOps, containerization, and cloud services.
9. Fully develop and implement a live, working DIY capstone project from scratch to the final production stage.
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!
“Sinopsis” puede pertenecer a otra edición de este título.
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Vendedor de IberLibro desde 12 de octubre de 2005
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