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Price: 2123.00 RUB
Machine Learning: Building Robust AI Models – A Practical Guide
In the ever-evolving landscape of artificial intelligence, creating models that are not only powerful but also reliable is a critical challenge. This book, Machine Learning: Building Robust AI Models, authored by Yada Pruksachatkun, Matthew MacCartir, and Subhabrata Majumdar, serves as a hands-on manual for developing ML systems that are sustainable, secure, and interpretable.
The authors delve into the core aspects of building trustworthy models, covering topics such as identifying vulnerabilities and biases, assessing algorithmic transparency, defending against adversarial attacks, and managing technical debt in ML projects. The guide is designed to help practitioners understand how modern approaches to fairness, interpretability, and safety function in real-world environments. It emphasizes practical application, showing how these concepts work when models face shifting conditions, noisy data, and human-centric use cases.
Whether you are a data scientist, ML engineer, or researcher, this book provides actionable insights for constructing AI systems that stand up to scrutiny and operate dependably. Priced at 2,123.00 RUR, it is a valuable resource for anyone committed to building robust machine learning solutions.
