Author: Dylan Tong

Data-centric AI (DCAI) has been described as the discipline of systematically engineering the data used to build an AI system. It prescribes prioritizing improving data quality over tweaking algorithms to improve machine learning models. In this post, explore a DCAI solution built on Snowflake and Amazon SageMaker to serve as a factory for predictive analytics solutions. Learn about Snowflake’s integrations with SageMaker and get hands-on resources to help you put these capabilities into practice.

Organizations that have foresight into their business have a competitive advantage. Advanced analytics that enable foresight have historically required scarce resources to develop predictive models using techniques like machine learning. Traditionally, this is a difficult endeavor, but recent progress in ML automation has made democratization of ML a possibility. Learn about the value of augmenting analytics with ML through the Amazon SageMaker for Tableau Quick Start.

Deploying AI solutions with ML models into production introduces new challenges. Machine Learning Operations (MLOps) has been evolving rapidly as the industry learns to marry new ML technologies and practices with incumbent software delivery systems and processes. WordStream is a SaaS company using ML capabilities to help small and mid-sized businesses get the most out of their online advertising. Learn how Slalom developed ML architecture to help WordStream productionize their machine learning efforts.