Machine Learning for Network Engineers

Machine Learning for Network Engineers is a comprehensive guide designed to equip network engineers with the knowledge and skills needed to apply machine learning techniques to their field.

It bridges the gap between networking and machine learning, explaining complex concepts in an accessible manner.

The book covers essential machine learning algorithms and demonstrates their application in network optimization, security, and troubleshooting.

Through practical examples and case studies, readers learn to leverage machine learning for tasks such as network anomaly detection, traffic prediction, and automated configuration.

It empowers network engineers to harness the power of machine learning for enhanced network performance and efficiency.