Good day,
Can anyone perhaps give me an idea of how large datasets scikit-learn
algorithms typically can handle?
I have about 4 TB of structured data. I might be able to normalize that
down to say 1 TB if necessary. The tasks would typically be logistic
regression, Naive Bayes, k-Means and possible others.
Will scikit-learn algorithms be able to handle this on a fairly powerful
hardware setup?
At which point does it become necessary to look at distributed ML platforms
e.g. Mahout instead?
Best regards,
Helge
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