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Various small docs clarifications #20

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merged 7 commits into from
May 27, 2022

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ryandawsonuk
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Points that I noticed when running through this and which I felt would've made it clearer for me

@@ -18,7 +18,7 @@ Enter your Github Personal Access Token.

Select your github account, then cd4ml-scenarios and click "Create Pipeline"

At this step the pipeline will build, you can select the pipeline to see the individual steps execute. At the end the pipeline should be 'green' indicating that all the steps were successful (shown below).
At this step the pipeline will build, you can select the pipeline to see the individual steps execute. Jenkins will first index branches, [which can take time](https://support.cloudbees.com/hc/en-us/articles/360055870591-Multibranch-Pipeline-Branch-indexing-job-stuck-and-cannot-be-aborted). It will then checkout the code which [can also take a while](https://stackoverflow.com/questions/36017253/jenkins-git-fetch-timeout). It does get there eventually. At the end the pipeline should run and be 'green' indicating that all the steps were successful (shown below). If it times out then trigger a manual run.
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@ryandawsonuk ryandawsonuk May 26, 2022

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This is basically reporting my experience with docker desktop. FWIW I was testing before f4e6e02 but I suspect this is something that can come and go depending on network connection and github itself

@@ -35,7 +35,7 @@ being changed to something else.

Note in the lasso directory, there is a file called big_alpha.json which
corresponds to the 'big_alpha' that we typed into that text box. It has
an alpha parameter of 50 rather than 1 and so encourages sparseness
an alpha parameter of 50 rather than 1 and so [encourages sparseness](https://chrisalbon.com/code/machine_learning/linear_regression/effect_of_alpha_on_lasso_regression/)
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extra link offers clarification



6) Looks at the ml_pipeline_params directory. Similarly, it contains a default.json file.
6) Look at the ml_pipeline directory. Similarly, it contains a default.json file.
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There is no ml_pipeline_params directory, it means ml_pipeline


![GreenExperiment](../images/GreenExperiment.png)

This lets us use Jenkins like an [ML training orchestration platform](https://github.com/EthicalML/awesome-production-machine-learning#model-training-orchestration).

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This note helps to clarify that our use of Jenkins here is just an example/illustration

@ericnagler
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Looks great. Thanks for the update @ryandawsonuk !

@ericnagler ericnagler merged commit 4af7493 into ThoughtWorksInc:master May 27, 2022
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2 participants