Allie Feras

In this session we'll dive deep on best practices for managing enterprise-ready machine learning pipelines at scale in Snowflake. We'll cover the orchestration of training and inference workflows, model lifecycle management, administrative best practices, RBAC models, CI/CD pipelines and more. January Technologies will share how it used these tools to take its machine learning projects from experimentation to deployment.

Learn how the Anthology data science team used Snowflake ML to derive students’ behavioral “DNA” from click-level data and uncover common patterns to help our customers better understand their students. This presentation will cover how we experimented with feature creation, neural network autoencoding and unsupervised learning approaches. We incorporated Snowflake artifacts into our iterative development and machine learning operations framework, unblocking research on this previously underused data.