MLFlow Mastery
Advanced Techniques for Optimizing ML Pipelines and Infrastructure
Created by ChrisPicture yourself at the helm of a cutting-edge machine learning operation, where models are deployed with lightning speed, experiments are tracked with pinpoint accuracy, and your ML infrastructure scales effortlessly to meet any challenge. This isn't a far-off dream—it's the reality that awaits you with MLFlow Mastery. As a seasoned software engineer, you know the power of streamlined workflows and robust infrastructure. Now, it's time to apply that expertise to the world of machine learning. This book is your comprehensive guide to harnessing the full potential of MLFlow, taking you beyond the basics and into the realm of advanced techniques that will set you apart in the field. Dive deep into the intricacies of MLFlow's architecture, uncover the secrets of custom flavors, and master the art of distributed training. You'll learn how to implement CI/CD pipelines for your ML projects, optimize hyperparameters like never before, and create scalable inference systems that can handle anything you throw at them. From automated logging to model drift detection, from feature store setup to multi-model ensembles, this book leaves no stone unturned in your quest for ML excellence. Whether you're looking to enhance model interpretability, implement federated learning, or push the boundaries of what's possible with MLFlow plugins, you'll find the expert guidance you need right here. Get ready to elevate your ML game and become the go-to expert for optimizing machine learning workflows in your organization.
Est. Length
331 pages (18 chapters)
Language
English
Publication date
May 5, 2025
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