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by tunguz on 2020-02-04 (UTC).

IEEE Fraud @Kaggle Challenge 1st Place Solution with @rapidsai library:https://t.co/x125dun7kl#ml #ai #ds #machinelearning

— Bojan Tunguz (@tunguz) February 4, 2020
kagglelearningtutorial
by rapidsai on 2020-02-05 (UTC).

See how Kaggler Chris Deotte uses @rapidsai #cuML to accelerate knn 600x in @kaggle #GPU cloud compute environment and augments data for higher accuracy on MNIST - https://t.co/H9aPHCMCsP

— RAPIDS AI (@rapidsai) February 5, 2020
learningtooltutorial
by tunguz on 2020-02-06 (UTC).

I just compared t-SNE algorithm on #MNIST dataset in @kaggle kernels between #sklearn and @rapidsai. We are getting a 2000X speedup!https://t.co/pbFgCbQ7jZ

— Bojan Tunguz (@tunguz) February 6, 2020
learning
by tunguz on 2020-02-06 (UTC).

And today I've tried UMAP with @nvidia @rapidsai in @kaggle kernels. A speedup of 120 x is nothing to sneeze at, even though it's not as dramatic as the 2000 x speedup for t-SNE.https://t.co/iIA8UZekH5 pic.twitter.com/QVRdqJQWag

— Bojan Tunguz (@tunguz) February 6, 2020
learningtool

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