Hands-On Guide To Building Production Ready Intelligent Systems With End-To-End Machine Learning Engineering From Data Collection And Training To Deployment And Live Tuning For Real World Success
✔️ End-to-end ML engineering: data collection to deployment
This audiobook explains how to build an intelligent system from data collection, training, deployment, and live tuning. It’s designed for software engineers, data scientists, and technical managers who want real-world, production-ready ML systems.
✅ End-to-end lifecycle coverage: data collection, training, deployment, live tuning
✅ Real-world case studies from high-traffic systems
✅ Practical guidance for engineers, ML practitioners, and managers
✅ Techniques for monitoring and improving production performance
💡 What is a production-ready intelligent system and how do you deploy one? This handy guide covers the main concepts and practical steps. - Production-ready intelligent system architecture and data feedback loops - Deployment strategies for scalable, observable ML systems - Monitoring, metrics, and governance to maintain performance