Hi Dong,
We assembled a first, very small, Markdown document providing a
jump-start description using a kMeans example. I could already share it
with you to check if we are pointing in the right direction. I had a
look at the Flink contribution guidelines, however the flink-ml project
is somewhat "separate" from Flink and the same I think holds for the
documentation. How do you think it is better to proceed?
Best regards
Dario Bonino
On 1/19/22 09:36, Dong Lin wrote:
Hi Bonino,
Definitely, it will be great to build up the Flink ML docs together
based on your experience.
Thanks!
Dong
On Wed, Jan 19, 2022 at 4:32 PM Bonino Dario <dario.bon...@gmail.com>
wrote:
Hi Dong,
Thank you for the reply. Since we are actually experimenting with
the Flink ML libraries, If you think it's worth, we may contribute
some documentation, e.g., tutorial based on what we learn while
setting up our test project with Flink ML. Is it something that
might be of interest for you?
Best regards
Dario
On 1/18/22 04:51, Dong Lin wrote:
Hi Bonino,
Thanks for your interest!
Flink ML is currently ready for experienced algorithm developers
to try it out because we have setup the basic APIs and
infrastructure to develop algorithms. Five algorithms (i.e.
kmeans, naive bays, knn, logistic regression and one-hot encoder)
has been implemented in the last release. Their unit tests can be
found here
<https://github.com/apache/flink-ml/tree/master/flink-ml-lib/src/test/java/org/apache/flink/ml/feature>,
here
<https://github.com/apache/flink-ml/tree/master/flink-ml-lib/src/test/java/org/apache/flink/ml/clustering>
and here
<https://github.com/apache/flink-ml/tree/master/flink-ml-lib/src/test/java/org/apache/flink/ml/classification>,
which show how to use these algorithms (including
transform/fit/save/load). And from these unit tests you can find
implementation of these algorithms which can be used as reference
implementation to develop other algorithms of your interest.
We plan to setup a website for Flink ML to provide links to
example/tutorial similar to the Flink Statefun website (link
<https://nightlies.apache.org/flink/flink-statefun-docs-stable/>).
This website will likely be setup in March. We are currently
working on developing further infrastructure for benchmarking and
optimizing the machine learning algorithms in Flink ML.
Best Regards,
Dong
On Mon, Jan 17, 2022 at 8:57 PM Dawid Wysakowicz
<dwysakow...@apache.org> wrote:
I am adding a couple of people who worked on it. Hopefully,
they will be able to answer you.
On 17/01/2022 13:39, Bonino Dario wrote:
Dear List,
We are in the process of evaluating Flink ML version 2.0 in
the context of some ML task mainly concerned with
classification and clustering.
While algorithms for this 2 domains are already present,
although in a limited form (perhaps) in the latest release
of Flink ML, we did not found any example / documentation
that could guide our experiments.
Is some adoption example available, like code, tutorial or
any information that might help us in bootstrapping a Flink
ML 2 project?
Thank you very much
Best regards
--
Ing. Dario Bonino, Ph.D
e-m@il:dario.bon...@gmail.com
www:https://www.linkedin.com/in/dariobonino
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Ing. Dario Bonino, Ph.D
e-m@il:dario.bon...@gmail.com
www:https://www.linkedin.com/in/dariobonino
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e-m@il:dario.bon...@gmail.com
www:https://www.linkedin.com/in/dariobonino
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