Data Integration Machine Learning Modeling 
O'Reilly on Data
DECEMBER 12, 2019
For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML.
O'Reilly on Data
NOVEMBER 13, 2018
Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations.
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O'Reilly on Data
DECEMBER 19, 2018
We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.
O'Reilly on Data
FEBRUARY 4, 2019
In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. You can find full results from the survey in the free report “Evolving Data Infrastructure”.). Data Platforms.
O'Reilly on Data
MAY 21, 2019
Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. Use ML to unlock new data types—e.g.,
O'Reilly on Data
MARCH 20, 2019
Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.
CIO Business Intelligence
DECEMBER 10, 2024
Large language models (LLMs) just keep getting better. In just about two years since OpenAI jolted the news cycle with the introduction of ChatGPT, weve already seen the launch and subsequent upgrades of dozens of competing models. million on inference, grounding, and data integration for just proof-of-concept AI projects.
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