The Intelligence Stack: A Practical Guide from Foundations to Production - Couverture souple

Name: The Intelligence Stack: A Practical Guide from Foundations to Production
Author: Mathur, Garima; Singh, Shweta; Gupta, Shumali
ISBN: 9789999356534

Mathur, Garima ; Singh, Shweta ; Gupta, Shumali

9789999356534: The Intelligence Stack: A Practical Guide from Foundations to Production

Couverture souple

ISBN 10 : 9999356532 ISBN 13 : 9789999356534

Editeur : Eliva Press, 2026

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THE INTELLIGENCE STACK A Practical Guide from Foundations to Production Build AI systems that work—not just models that demonstrate. The Intelligence Stack is a practical, end-to-end guide to understanding, building, evaluating, and deploying modern Artificial Intelligence systems. Starting with the essential foundations of mathematics, Python, data preparation, and machine learning, the book progressively moves into deep learning, computer vision, sequence modelling, Transformers, Large Language Models, Retrieval-Augmented Generation, prompt engineering, and AI agents. Unlike approaches that focus only on increasingly sophisticated models, this book emphasizes the engineering discipline required to make AI systems reliable in practice. Readers learn how to select techniques that match the problem, prepare trustworthy data, design meaningful evaluations, identify leakage and failure modes, and move from experimentation to production. The journey continues through model deployment, scalability, monitoring, testing, MLOps, bias and interpretability, AI safety, and ethical and legal considerations. Five hands-on projects and industry case studies across financial services, healthcare, retail, manufacturing, and software engineering connect concepts to realistic applications. Whether you are a student beginning your AI journey, an engineer adding machine learning to your work, a practitioner responsible for deployed systems, or a learner building projects, The Intelligence Stack provides a structured path from foundations to production. Understand the mathematics. Build the models. Evaluate the evidence. Deploy with discipline.

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