ML in Production: Serverless and Painless

Big Data LDN 2019 | ML in Production: Serverless and Painless | Oliver Gindele
Course info
Level
Intermediate
Updated
Dec 13, 2019
Duration
33m
Table of contents
ML in Production: Serverless and Painless
Description
Course info
Level
Intermediate
Updated
Dec 13, 2019
Duration
33m
Description

Productionising machine learning pipelines can be a daunting and difficult task for Data Scientists. Fortunately, many novel tools and technologies have become available in the past years to address this issue and make it easier than ever to deploy ML models into production, without the need to configure servers. In this session, Oliver Gindele will walk through some of the best serverless options on how to operationalise ML pipelines within the Tensorflow ecosystem and on Google Cloud Platform based on actual case studies. One of these real-life case studies will dive into the journey of a global cosmetics brand to become packaging-free with the help of ML. The first step towards this goal allows customers to view product information simply by taking a picture. This completely eliminates the need for packaging and labels in stores. However, in order to do this effectively, an accurate image classification model, accessible on mobile phones, is needed. This session will cover the details of the end-to-end machine learning pipeline that was created to deliver and update performant ML models to mobile users.

About the author
About the author

Big Data LDN is the UK’s largest data and analytics conference and exhibition.

More from the author
The Next Generation of Data Architecture
Intermediate
23m
Dec 20, 2019
Converting the CDO to a Profit Centre
Intermediate
20m
Dec 17, 2019
AI-driven Retail for the 21st Century
Intermediate
23m
Dec 17, 2019
More courses by Big Data LDN