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Interview about career/book
(Oct 2018, coffee with a Googler) Lead your Company Towards Data-Powered Innovation (Google Cloud Next, Sep 2020)
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Machine Learning Design Patterns for ML Ops (Aug 2020, virtual Google Developer Group DevFest)
Machine Learning and Bayesian Statistics in Minutes: How Data Scientists use BigQuery (Sep 2019, Future of your Data Warehouse)
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Explaining Image ML Model predictions (Cloud On Air, April 2021)
Feature engineering in BigQuery and TensorFlow 2.0/Keras (Nov 2019, Kirkland)
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How to Automatically Optimize Retail Sales with BigQuery ML (Apr 2019, Cloud On Air)
MLOps: How to automate CI/CDE in Machine using Kubeflow Pipelines (Feb 2020, Seattle)
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Leverage AI on the Cloud to Transform Your Business (July 2018, Cloud Next)
End-to-End Machine Learning With TensorFlow on Google Cloud Platform (Mar 2018, Cloud On Air)
Training Image & Text Classification Models Faster with TPUs (Mar 2019, San Francisco)
Cloud OnAir: Processing forms automatically using Document AI (Nov 2020)
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Using public datasets on Google Cloud Platform (Sep 2018, Cloud On Air)
The Digital Native Podcast on what my team at Google (Solution Engineering) does, where I see the industry going. June 2020
Infuse Your Business with Machine Learning (Cloud Next, March 2017)
What's New in TensorFlow, and How GCP Developers Benefit (Apr 2019, Cloud Next)
Data Science on the Cloud in Python (July 2016, PyData Singapore)
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The Zen guide to getting your data ready for Machine Learning (Dec 2017, Tel Aviv)
End-to-end machine learning with TensorFlow on Google Cloud Platform (Feb 2018, Chicago)
Design Patterns for ML infrastructure (Feb 2021, Data Works, MD)
Crossing the Chasm: Patterns to Develop, Operationalize, and Maintain ML Models (Cloud Next 2018)
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BigQuery GIS product intro (July 2018)
How all your data leads to Cloud Machine Learning (July 2018, San Francisco)
Auto-awesome: advanced data science on Google Cloud Platform (Mar 2017, Cloud Next)
Training Image & Text Classification Models Faster with TPUs on Cloud ML Engine (Nov 2018, Cloud AI Huddle)
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