When Machine Learning meets Data Privacy - Episode 2 with Cat Coode

MLOps.community - A podcast by Demetrios Brinkmann

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What are regulations saying about data privacy? We are already aware of the importance of using Machine Learning to improve businesses, nevertheless to feed Machine Learning, data is a must, and in many cases, this data might even be considered sensitive information. So, does this mean that with new privacy regulations, access to data will be more and more difficult? ML and Data Science have their days counted? Or Will Machine beat privacy? To answer all these questions I’ve invited Cat Coode, an expert on Data Privacy regulations, to join me in this episode, and help us sort out these questions! Don’t forget to subscribe to the Mlops.community slack and if you’re looking for privacy-preserving solutions, show us some love and give a star to the Synthetic data open-source repo (https://github.com/ydataai/ydata-synthetic) Useful links: For more on Cat's work, you can have a look at catcoode.com or connect through LinkedIn. Original Privacy by design definition: https://www.ipc.on.ca/wp-content/uploads/resources/7foundationalprinciples.pdf

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