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Saturday, October 20 • 4:00pm - 4:30pm
Introducing Cranial: The Machine learning Engineer’s Open Source Toolbox

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An introduction to the open-source Python code library and Framework for accelerating the Data-Science-to-Production pipeline and delivering scalable, distributed AI- and Machine-Learning-backed services. It provides:
- Standardized interfaces for Data Storage & Retrieval with many Databases, Protocols, and Filesystems;
- Synchronous and Asynchronous Messaging with or without brokers;
- Wrappers for ML models providing interoperability with these Data & Messaging Services.

This Python Programmer's toolkit was developed at Tribune Publishing and powers successful Content Recommendation services that learn from user behavior in real-time, for the Chicago Tribune and other major newspapers, but was developed as a general solution for delivering Data Pipelines with a focus on the needs of high-speed, high volume Online Learning Models.

This presentation will identify how Cranial fits into the current ecosystem of Data Science & Engineering platforms, comparing and contrasting to Airflow, Spark, Tensorflow, and related technologies. We'll give an overview of the capabilities provided and how to use them to solve common problems, and walk through the specific implementation of the Tribune Content Recommendation System with Cranial and Tensorflow. Finally, we'll discuss future goals of the Cranial project and how users can shape its future direction.

avatar for Matt Chapman

Matt Chapman

Manager & Data engineering, mPulse Mobile
Matt is currently the Manager of Data Engineering at mPulse Mobile, a company providing innovative messaging solutions to Health Care providers. Previously, Matt was the founding Data Engineer for Tribune Interactive’s Data Science team, designing and implementing an in-house News... Read More →

Saturday October 20, 2018 4:00pm - 4:30pm
Ballroom # 406