ML in Production: Serverless and Painless
Learn serverless machine learning for production! Oliver Gindele teaches practical, pain-free ML deployment at Big Data LDN 2019.
Course Content
ML in Production: Serverless and Painless is an intermediate-level Pluralsight course taught by Big Data LDN. It runs 33m, is taught in English, and includes a certificate of completion. It is a paid course, first published June 2021.
Productionizing machine learning pipelines can be a challenging task for data scientists. Discover how to streamline the deployment of your ML models into production with the latest tools and technologies. Learn how to operationalize ML pipelines within the TensorFlow ecosystem and on Google Cloud Platform, all without the complexities of server configuration.
Join Oliver Gindele for a session featuring real-world case studies demonstrating best practices for ML deployment.
One compelling example explores how a global cosmetics brand is leveraging machine learning to achieve a packaging-free future. The initial step involves enabling customers to instantly access product information by simply taking a picture, eliminating the need for traditional packaging and labels in stores.
This requires a highly accurate image classification model accessible on mobile devices. This session details the end-to-end machine learning pipeline developed to reliably deliver and update high-performing ML models to mobile users. Explore how serverless computing can simplify your MLOps workflow and accelerate your model deployment. Gain insights into practical strategies for deploying TensorFlow models and building robust ML pipelines on Google Cloud.
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