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Data science

Data science ideas and resources.

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Core technologies and tools for AI, big data, and cloud computing

By Ben Lorica | February 11, 2019

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Deep automation in machine learning

By Ben Lorica, Mike Loukides | December 19, 2018

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Handling real-time data operations in the enterprise

By Jesse Anderson | September 24, 2018

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It’s time to establish big data standards

By Rohit Jain | August 16, 2018

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Case studies in data ethics

By Mike Loukides, Hilary Mason, DJ Patil | August 7, 2018

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Data collection and data markets in the age of privacy and machine learning

By Ben Lorica | July 18, 2018

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Testing machine learning explanation techniques

By Patrick Hall, Navdeep Gill, Lingyao Meng | June 26, 2018

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5 key drivers for getting more value from your data

By Michael Li, Matt Maccaux | June 5, 2018

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How to build analytic products in an age when data privacy has become critical

By Ben Lorica | May 3, 2018

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How to run a custom version of Spark on hosted Kubernetes

By Holden Karau, Alena Hall | April 19, 2018

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It’s time for data ethics conversations at your dinner table

By Lucy C. Erickson, Natalie Evans Harris, Meredith M. Lee | April 3, 2018

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How companies around the world apply machine learning

By Ben Lorica | April 3, 2018

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Interpreting predictive models with Skater: Unboxing model opacity

By Pramit Choudhary | March 22, 2018

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Data governance and the death of schema on read

By Barbara Eckman | March 22, 2018

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Identifying budding big data talent in your company

By Michael Li | March 8, 2018

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Comparing production-grade NLP libraries: Accuracy, performance, and scalability

By Saif Addin Ellafi | February 28, 2018