Build a Machine Learning Platform (MEAP) by Benjamin Tan Wei Hao(.PDF)
File Size: 42.5 MB
Build a Machine Learning Platform (From Scratch) (MEAP v6) by Benjamin Tan Wei Hao, Shanoop Padmanabhan, Varun Mallya
Requirements: .PDF reader, 42.5 MB | True PDF
Overview: Get your Machine Learning models out of the lab and into production! Delivering a successful Machine Learning project is hard. Build a Machine Learning Platform (From Scratch) makes it easier. In it, you’ll design a reliable ML system from the ground up, incorporating MLOps and DevOps along with a stack of proven infrastructure tools including Kubeflow, MLFlow, BentoML, Evidently, and Feast. Build a Machine Learning Platform (From Scratch) teaches you to set up and run a production-quality Machine Learning system using open source tools. Chapter-by-chapter, you’ll assemble a delivery pipeline for an image classifier and a recommendation system, learning best practices as you go. You’ll get hands-on experience with the most important parts of the Machine Learning workflow, including orchestrating pipelines; model training, inference, and serving; and monitoring and explainability. Soon, you’ll be deploying models that are fast to production and easy to maintain and scale. For data scientists or software engineers who know how to program in Python.
Genre: Non-Fiction > Tech & Devices
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