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Deep learning and Artificial Intelligence (AI) have moved well beyond science fiction into the cutting edge of internet and enterprise computing. In this 4-part blog series, we are going to explore deep learning, and the role database selection plays in successfully applying deep learning to business problems.

The timeline for compliance with the European Union's General Data Protection Regulation (GDPR) is fast approaching. From May 25th 2018, any organization failing to satisfy the new regulation faces fines of up to 4% of global revenues, or €20m - whichever is greater - as well as the potential suspension of any further data processing activities. Irrespective of whether you have a physical presence in the EU or not, if you are handling EU citizen data in any way, you are subject to the GDPR.

Transactions are important. Any database needs to offer transactional guarantees to enforce data integrity. But they don't all do it in the same way - different database technologies take different approaches.

The developer landscape has dramatically changed in recent years. It used to be fairly common for us developers to run all of our tools (databases, web servers, development IDEs…) on our own machines, but cloud services such as GitHub, MongoDB Atlas and AWS Lambda are drastically changing the game. They make it increasingly easier for developers to write and run code anywhere and on any device with no (or very few) dependencies.

Over the last four months, I attended an immersive data science program at Galvanize in San Francisco. As a graduation requirement, the last three weeks of the program are reserved for a student-selected project that puts to use the skills learned throughout the course. The project that I chose to tackle utilized natural language processing in tandem with sentiment analysis to parse and classify news articles.

MongoDB 3.6 is now Generally Available (GA), and ready for production deployment. In this short blog series, MongoDB be taking you on a whirlwind tour of what's new in this latest release.

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