Re: Beam ML Use Cases - Google Summer of Code 2023

2023-09-18 Thread Danielle Syse via dev
m/posts/apache-beam_apache-beam-ml-use-cases-gsoc-2023-report-activity-7109551417610158085-q48T?utm_source=share&utm_medium=member_desktop> On Fri, Sep 15, 2023 at 8:09 PM Ahmet Altay wrote: > Thank you for your hard work and writing this Reeba! > > @Danielle Syse - could we please

Re: Beam ML Use Cases - Google Summer of Code 2023

2023-09-15 Thread Ahmet Altay via dev
. >>> >>> Here are the use cases I built during the summer: >>> 1. Batch Image Processing | GitHub >>> <https://github.com/reeba212/beam/blob/master/examples/notebooks/beam-ml/image_processing_tensorflow.ipynb> >>> 2. Streaming Sentiment Analysis |

Re: Beam ML Use Cases - Google Summer of Code 2023

2023-09-13 Thread Danny McCormick via dev
; Here are the use cases I built during the summer: >> 1. Batch Image Processing | GitHub >> <https://github.com/reeba212/beam/blob/master/examples/notebooks/beam-ml/image_processing_tensorflow.ipynb> >> 2. Streaming Sentiment Analysis | GitHub >> <https://github.com/r

Re: Beam ML Use Cases - Google Summer of Code 2023

2023-09-13 Thread XQ Hu via dev
during the summer: > 1. Batch Image Processing | GitHub > <https://github.com/reeba212/beam/blob/master/examples/notebooks/beam-ml/image_processing_tensorflow.ipynb> > 2. Streaming Sentiment Analysis | GitHub > <https://github.com/reeba212/beam/blob/master/examples/notebooks/

Re: Beam ML Use Cases - Google Summer of Code 2023

2023-09-13 Thread Reeba Qureshi
che-beam-gsoc-2023-report-edeb313d43ba> . Here are the use cases I built during the summer: 1. Batch Image Processing | GitHub <https://github.com/reeba212/beam/blob/master/examples/notebooks/beam-ml/image_processing_tensorflow.ipynb> 2. Streaming Sentiment Analysis | GitHub <https://gith

Re: Beam ML

2017-01-11 Thread Suneel Marthi
Mahout would have CSR support in the upcoming release as well as hybrid GPU/CPU execution depending on the work load. This discussion is better moved to dev@mahout, since the Mahout project has long abstracted out Spark, Flink and H2O for distributed linear algebra; and we are now adding swappable

Re: Beam ML

2017-01-11 Thread Kam Kasravi
Thanks Andrew - Since you're quite familiar with how Mahout backends (flink, spark, h20) bind and enable DRM and the API Mahout/Samsara exposes - I think the end goal would be to surface a JAVA/Python API as well as outline a declarative syntax that the various runners can adhere to (perhaps via s

Re: Beam ML

2017-01-11 Thread Andrew Musselman
That's right; what other info do you think would be useful? On Tue, Jan 10, 2017 at 11:09 AM, Kam Kasravi wrote: > Thanks Andrew > I think more information about the DRM operations and how persistence > would be done at the runner level. It looks like HDFS or spark caching is > currently being u

Re: Beam ML

2017-01-10 Thread Kam Kasravi
Thanks Andrew I think more information about the DRM operations and how persistence would be done at the runner level. It looks like HDFS or spark caching is currently being used? On Monday, January 9, 2017 6:04 PM, Andrew Musselman wrote: Hello Beam Team, Thought you might be intere

Re: Beam ML

2017-01-09 Thread Andrew Musselman
Hello Beam Team, Thought you might be interested in the work we've been doing on Mahout, such as the distributed linear algebra DSL/front-end that can use multiple back-ends for compute (Spark, Flink, H2O now). See https://mahout.apache.org/users/environment/out-of-core-reference.html for an intro

Re: Beam ML

2017-01-09 Thread Kam Kasravi
Hi Vladisav I'm the author of the design document. An area we stalled on was creating a common low level linear algebra library that would also include optimizations like MKL but across platforms and GPUs. Additionally there are efforts underway that provide a scoring API vs a training API. -

Re: Beam ML

2017-01-06 Thread Jean-Baptiste Onofré
Hi Vladisav We would love to have contributions around this. Basically, what I have in mind first is a machine learning extension providing the DoFn/PTransform implementing algorithms (KMeans, regression, ...). The DSL will come after IMHO. Regards JB On 01/06/2017 04:07 PM, Vladisav Jelis

Beam ML

2017-01-06 Thread Vladisav Jelisavcic
Hi everyone, what is the current status on BEAM-478 and BEAM-303 (machine learning learning DSL and related functions)? I would like to start contributing in this direction. I found this design document: https://docs.google.com/document/d/17cRZk_yqHm3C0fljivjN66MbLkeKS1yjo4PBECHb-xA/edit#heading=