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Posted to user@madlib.apache.org by Frank McQuillan <fm...@pivotal.io> on 2017/08/30 18:39:32 UTC
New 1.12 Jupiter notebooks available
Hello,
Now that 1.12 has shipped, I want to remind you of Jupiter notebooks with
the new 1.12 features posted to:
https://github.com/apache/madlib-site/tree/asf-site/community-artifacts
The goal of these data science notebooks is to help you get started on the
new features by showing examples of usage that you can copy. Many of them
reflect the examples in the user docs at:
http://madlib.apache.org/docs/latest/index.html
The new 1.12 notebooks that have been added are:
neural nets (general MLP usage)
https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/mlp-v1.ipynb
neural nets (demo uses the popular MNIST dataset, which consists of 70,000
hand written digits and is used for classification)
https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/MLP.ipynb
graph/all pairs shortest path
https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/APSP-v1.ipynb
graph measures (closeness, diameter, average path length, in-out degree)
https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/Graph-measures-v1.ipynb
graph/breadth-first search
https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/Breadth-first-search-v1.ipynb
graph/weakly connected components
https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/Weakly-connected-cpts-v2.ipynb
stratified sampling
https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/stratified-sampling-v1.ipynb
train-test split
https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/Train-test-split-v1.ipynb
If you have your own examples that you would like to add the repo, you are
most welcome to do so.
Frank
Re: New 1.12 Jupiter notebooks available
Posted by Frank McQuillan <fm...@pivotal.io>.
Hi Aaron,
There is not a big emphasis on setting up the database itself, since we
mostly assume it is set up. Maybe not a good assumption.
There are example connection strings in the notebooks themselves.
We provide a Docker image with necessary dependencies required to compile
and test MADlib on PostgreSQL 9.6.
https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Developers#QuickStartGuideforDevelopers-Dock
https://cwiki.apache.org/confluence/display/MADLIB/Installation+Guide
https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Users
https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Developers
If you would like to add more content, or modify what is there, to make it
more accessible, that would be great.
Regarding the forum of deeplearning.ai courses, do you have a link? This
link leads to the signup.
Frank
On Wed, Aug 30, 2017 at 11:57 AM, FENG, Xixuan (Aaron) <
xixuan.feng@gmail.com> wrote:
> This is great!
>
> Do we have documentation about setting up databases to connect with
> Jupyter Notebook to run? I think not many python users have done that.
>
> The MLP examples are especially interesting. I suggest we share them on
> the forum of deeplearning.ai courses. There are so many enthusiasts who
> may be interested in these.
>
> Aaron
>
> On Wed, Aug 30, 2017 at 11:39 AM, Frank McQuillan <fm...@pivotal.io>
> wrote:
>
>> Hello,
>>
>> Now that 1.12 has shipped, I want to remind you of Jupiter notebooks with
>> the new 1.12 features posted to:
>> https://github.com/apache/madlib-site/tree/asf-site/community-artifacts
>>
>> The goal of these data science notebooks is to help you get started on
>> the new features by showing examples of usage that you can copy. Many of
>> them reflect the examples in the user docs at:
>> http://madlib.apache.org/docs/latest/index.html
>>
>> The new 1.12 notebooks that have been added are:
>>
>> neural nets (general MLP usage)
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/mlp-v1.ipynb
>>
>> neural nets (demo uses the popular MNIST dataset, which consists of
>> 70,000 hand written digits and is used for classification)
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/MLP.ipynb
>>
>> graph/all pairs shortest path
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/APSP-v1.ipynb
>>
>> graph measures (closeness, diameter, average path length, in-out degree)
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/Graph-measures-v1.ipynb
>>
>> graph/breadth-first search
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/Breadth-first-search-v1.ipynb
>>
>> graph/weakly connected components
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/Weakly-connected-cpts-v2.ipynb
>>
>> stratified sampling
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/stratified-sampling-v1.ipynb
>>
>> train-test split
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/Train-test-split-v1.ipynb
>>
>> If you have your own examples that you would like to add the repo, you
>> are most welcome to do so.
>>
>> Frank
>>
>
>
Re: New 1.12 Jupiter notebooks available
Posted by Frank McQuillan <fm...@pivotal.io>.
Hi Aaron,
There is not a big emphasis on setting up the database itself, since we
mostly assume it is set up. Maybe not a good assumption.
There are example connection strings in the notebooks themselves.
We provide a Docker image with necessary dependencies required to compile
and test MADlib on PostgreSQL 9.6.
https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Developers#QuickStartGuideforDevelopers-Dock
https://cwiki.apache.org/confluence/display/MADLIB/Installation+Guide
https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Users
https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Developers
If you would like to add more content, or modify what is there, to make it
more accessible, that would be great.
Regarding the forum of deeplearning.ai courses, do you have a link? This
link leads to the signup.
Frank
On Wed, Aug 30, 2017 at 11:57 AM, FENG, Xixuan (Aaron) <
xixuan.feng@gmail.com> wrote:
> This is great!
>
> Do we have documentation about setting up databases to connect with
> Jupyter Notebook to run? I think not many python users have done that.
>
> The MLP examples are especially interesting. I suggest we share them on
> the forum of deeplearning.ai courses. There are so many enthusiasts who
> may be interested in these.
>
> Aaron
>
> On Wed, Aug 30, 2017 at 11:39 AM, Frank McQuillan <fm...@pivotal.io>
> wrote:
>
>> Hello,
>>
>> Now that 1.12 has shipped, I want to remind you of Jupiter notebooks with
>> the new 1.12 features posted to:
>> https://github.com/apache/madlib-site/tree/asf-site/community-artifacts
>>
>> The goal of these data science notebooks is to help you get started on
>> the new features by showing examples of usage that you can copy. Many of
>> them reflect the examples in the user docs at:
>> http://madlib.apache.org/docs/latest/index.html
>>
>> The new 1.12 notebooks that have been added are:
>>
>> neural nets (general MLP usage)
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/mlp-v1.ipynb
>>
>> neural nets (demo uses the popular MNIST dataset, which consists of
>> 70,000 hand written digits and is used for classification)
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/MLP.ipynb
>>
>> graph/all pairs shortest path
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/APSP-v1.ipynb
>>
>> graph measures (closeness, diameter, average path length, in-out degree)
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/Graph-measures-v1.ipynb
>>
>> graph/breadth-first search
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/Breadth-first-search-v1.ipynb
>>
>> graph/weakly connected components
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/Weakly-connected-cpts-v2.ipynb
>>
>> stratified sampling
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/stratified-sampling-v1.ipynb
>>
>> train-test split
>> https://github.com/apache/madlib-site/blob/asf-site/communit
>> y-artifacts/Train-test-split-v1.ipynb
>>
>> If you have your own examples that you would like to add the repo, you
>> are most welcome to do so.
>>
>> Frank
>>
>
>
Re: New 1.12 Jupiter notebooks available
Posted by "FENG, Xixuan (Aaron)" <xi...@gmail.com>.
This is great!
Do we have documentation about setting up databases to connect with Jupyter
Notebook to run? I think not many python users have done that.
The MLP examples are especially interesting. I suggest we share them on the
forum of deeplearning.ai courses. There are so many enthusiasts who may be
interested in these.
Aaron
On Wed, Aug 30, 2017 at 11:39 AM, Frank McQuillan <fm...@pivotal.io>
wrote:
> Hello,
>
> Now that 1.12 has shipped, I want to remind you of Jupiter notebooks with
> the new 1.12 features posted to:
> https://github.com/apache/madlib-site/tree/asf-site/community-artifacts
>
> The goal of these data science notebooks is to help you get started on the
> new features by showing examples of usage that you can copy. Many of them
> reflect the examples in the user docs at:
> http://madlib.apache.org/docs/latest/index.html
>
> The new 1.12 notebooks that have been added are:
>
> neural nets (general MLP usage)
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/mlp-v1.ipynb
>
> neural nets (demo uses the popular MNIST dataset, which consists of 70,000
> hand written digits and is used for classification)
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/MLP.ipynb
>
> graph/all pairs shortest path
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/APSP-v1.ipynb
>
> graph measures (closeness, diameter, average path length, in-out degree)
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/Graph-measures-v1.ipynb
>
> graph/breadth-first search
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/Breadth-first-search-v1.ipynb
>
> graph/weakly connected components
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/Weakly-connected-cpts-v2.ipynb
>
> stratified sampling
> https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/
> stratified-sampling-v1.ipynb
>
> train-test split
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/Train-test-split-v1.ipynb
>
> If you have your own examples that you would like to add the repo, you are
> most welcome to do so.
>
> Frank
>
Re: New 1.12 Jupiter notebooks available
Posted by "FENG, Xixuan (Aaron)" <xi...@gmail.com>.
This is great!
Do we have documentation about setting up databases to connect with Jupyter
Notebook to run? I think not many python users have done that.
The MLP examples are especially interesting. I suggest we share them on the
forum of deeplearning.ai courses. There are so many enthusiasts who may be
interested in these.
Aaron
On Wed, Aug 30, 2017 at 11:39 AM, Frank McQuillan <fm...@pivotal.io>
wrote:
> Hello,
>
> Now that 1.12 has shipped, I want to remind you of Jupiter notebooks with
> the new 1.12 features posted to:
> https://github.com/apache/madlib-site/tree/asf-site/community-artifacts
>
> The goal of these data science notebooks is to help you get started on the
> new features by showing examples of usage that you can copy. Many of them
> reflect the examples in the user docs at:
> http://madlib.apache.org/docs/latest/index.html
>
> The new 1.12 notebooks that have been added are:
>
> neural nets (general MLP usage)
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/mlp-v1.ipynb
>
> neural nets (demo uses the popular MNIST dataset, which consists of 70,000
> hand written digits and is used for classification)
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/MLP.ipynb
>
> graph/all pairs shortest path
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/APSP-v1.ipynb
>
> graph measures (closeness, diameter, average path length, in-out degree)
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/Graph-measures-v1.ipynb
>
> graph/breadth-first search
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/Breadth-first-search-v1.ipynb
>
> graph/weakly connected components
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/Weakly-connected-cpts-v2.ipynb
>
> stratified sampling
> https://github.com/apache/madlib-site/blob/asf-site/community-artifacts/
> stratified-sampling-v1.ipynb
>
> train-test split
> https://github.com/apache/madlib-site/blob/asf-site/
> community-artifacts/Train-test-split-v1.ipynb
>
> If you have your own examples that you would like to add the repo, you are
> most welcome to do so.
>
> Frank
>