Building Intelligent Systems Using Machine Learning and Deep Learning: Security, Applications and Its Challenges

Grab the future of intelligent technology with Building Intelligent Systems Using Machine Learning and Deep Learning: Security, Applications and Its Challenges by Frank Columbus — an essential guide for engineers, architects, and decision-makers looking to harness AI responsibly and effectively.

This authoritative volume cuts through complexity to explain how machine learning and deep learning power modern systems, while exposing the security risks and operational challenges that come with scale. Through clear explanations and industry-relevant examples, Columbus examines model architectures, deployment strategies, threat surfaces, privacy concerns, and mitigation techniques that matter to practitioners in enterprises across North America, Europe, Asia-Pacific and beyond.

You’ll discover practical insights on designing resilient AI systems for real-world applications — from healthcare and finance to IoT and autonomous systems — alongside an honest appraisal of limitations, biases, and regulatory implications. The book balances technical depth with strategic perspective, helping readers translate algorithmic advances into secure, maintainable Books and services.

Whether you’re a data scientist refining models, a CTO evaluating AI risk, or a student building domain expertise, this book delivers actionable guidance: best practices for secure ML pipelines, methods to detect adversarial behavior, and approaches for continuous monitoring and governance. It also highlights emerging trends and the challenges organizations must prepare for as AI adoption accelerates globally.

Confidently navigate the intersection of innovation and safety — add Building Intelligent Systems Using Machine Learning and Deep Learning by Frank Columbus to your library and start building intelligent, secure systems today.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.