@cevenif: 90% of machine learning tutorials on the market are actually misleading you—what's the point of just training a model? If it can't go into production, all the earlier effort is wasted. Seriously, I've seen too many people fall into this trap: they follow tutorials and train models like crazy, but when they put them into real-world environments, they immediately break—they don't know how to deploy, can't set up monitoring, and scalability is a mess. Harvard University directly...

90% of machine learning tutorials on the market are actually misleading you—what's the point of just training a model? If it can't go into production, all the earlier effort is wasted. Seriously, I've seen too many people fall into this trap: they follow tutorials and train models like crazy, but when they put them into real-world environments, they immediately break—they don't know how to deploy, can't set up monitoring, and scalability is a mess. Harvard University has directly open-sourced a textbook called "Machine Learning Systems" specifically to fill this gap. No paid courses, no fees—just grab it directly from GitHub. What makes this book great? It doesn't teach you how to tune hyperparameters; instead, it teaches you how to actually bring an AI system from 0 to 1, covering the complete chain from edge devices to the cloud. Specifically, you can dig into these hardcore topics: - System design: how to build scalable and maintainable ML architectures, not just toy projects - Data engineering: the full pipeline of collection, labeling, and processing—if your data is bad, even the best model is useless - Model deployment: best practices for moving from prototype to production—99% of tutorials leave this blank - MLOps monitoring: how to keep your system healthy after deployment and ensure long-term reliable operation - Edge AI: how to run models efficiently on mobile, embedded, and IoT devices - Hands-on projects: a companion TinyTorch framework with practical exercises—not just theory without practice You can read it online or download the PDF. If you really want to master the AI systems engineering track, this one is a must-have. Training is just getting a ticket; being able to deploy, maintain, and scale—that's real skill. https://github.com/harvard-edge/cs249r_book…