Data Science
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Data is not always useful and it doesn't matter how much of it you have.
There’s no mathematical tool to tell you if your hypothesis is true; you can only see whether it is consistent with the data, and if the data is sparse or unclear, your conclusions are uncertain.
- Logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
- Reproducible Data Science at Scale.
- Language and runtime for distributed, incremental data processing in the cloud.