scale.bythebay.io: Rajesh Muppalla, Continuous Delivery Principles for Machine Learning

ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Scale By the Bay 2019 is held on November 13-15 in sunny Oakland, California, on the shores of Lake Merritt: https://scale.bythebay.io. Join us! ----- Real world Software Engineering is an iterative process and one of its main objectives is to get changes all of types - including new features, configuration changes, bug fixes and experiments into production and into the hands of the users, safely, quickly and in a sustainable way. Continuous Delivery (CD), a software engineering discipline, with its principled approach allows you to solve this exact problem. The core idea of CD is to create a repeatable, reliable and incrementally improving process for taking software from concept to the end user. Like software development, building real world machine learning (ML) algorithms is an also an iterative process with a similar objective - How do I get my ML algorithms into production and in the hands of the users in a safe, quick and sustainable way. The current process of building models, testing and deploying them into production is at best an ad-hoc process in most companies. At Indix, while building the Google of Products, we have had some good success in combining the best practices of continuous delivery in building our machine learning pipelines using open source tools and frameworks. The talk will not focus on the theory of ML or about choosing the right ML algorithm but specifically on the last mile problem of taking models to production and the lessons learned while applying the concept of CD to ML.. Here a…

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