The MOA Team

MOA is an open source data mining tool for massive data, related to the WEKA project, written in Java, while scaling to more demanding problems.

[The MOA Team @moadatamining]

New Release of MOA 23.04 https://t.co/aJHQmJyyEL

[The MOA Team @moadatamining]

New Release of MOA 21.07 https://t.co/JacT87f8tH

[The MOA Team @moadatamining]

Feature Analysis Tab https://t.co/R2dJKbe6cj

[The MOA Team @moadatamining]

New Release of MOA 20.12 https://t.co/skKXkgyKT9

[The MOA Team @moadatamining]

New Release of MOA 20.07 https://t.co/eB6nEZKPnS

[The MOA Team @moadatamining]

Streaming Random Patches https://t.co/Gx2PJX8g9o

[The MOA Team @moadatamining]

scikit-multiflow: machine learning for data streams in Python https://t.co/Azino6XlS2

[The MOA Team @moadatamining]

How to use MOA in Docker https://t.co/t7Yd4u8C0p

[The MOA Team @moadatamining]

New “LITE” Mode for Beginners https://t.co/88SE2bSURY

[The MOA Team @moadatamining]

New Release of MOA 19.04 https://t.co/BBxSdQiaMy

[The MOA Team @moadatamining]

How to use Jupyter Notebooks with MOA https://t.co/g4O0ceoDOv

[The MOA Team @moadatamining]

Online Comments Available for the MOA Book https://t.co/DJVgYB7lIe

[The MOA Team @moadatamining]

New Release of MOA 18.06 https://t.co/cSPqFvMWfu

[The MOA Team @moadatamining]

Using MOA interactively with the new Java Shell tool https://t.co/Y9ZMU40dX5

[The MOA Team @moadatamining]

Active Learning Tab https://t.co/WBNzYLRXrI

[The MOA Team @moadatamining]

“Machine Learning for Data Streams with Practical Examples in MOA” Book https://t.co/nbIKED9DLH

[The MOA Team @moadatamining]

MOA with Apache Flink https://t.co/VP8J9yDsw1

[The MOA Team @moadatamining]

Adaptive Random Forest https://t.co/zYY6rpaAXF

[The MOA Team @moadatamining]

New Release of MOA 17.06 https://t.co/7MAMRi7Tc8

[The MOA Team @moadatamining]

New Release of MOA 16.04 https://t.co/VyPdO1yRYa