doc: AutoML #1158

chuyang-deng · 2019-12-10T21:44:11Z

Issue #, if available:

Description of changes:
Adding documentations to README and automl/README

Merge Checklist

Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your pull request.

I have read the CONTRIBUTING doc
I used the commit message format described in CONTRIBUTING
I have added tests that prove my fix is effective or that my feature works (if appropriate)
I have updated any necessary documentation (if appropriate)

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

update with aws:master

sagemaker-bot · 2019-12-10T21:49:36Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-10T22:03:26Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-10T22:12:36Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-10T22:32:05Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

laurenyu · 2019-12-10T22:11:48Z

README.rst

+SageMaker Autopilot
+-------------------
+
+Amazon SageMaker Autopilot is an automated machine learning (commonly referred to as AutoML) solution for tabular


I would move "(commonly referred to as AutoML)" to after "solution". Also, put "AutoML" in quotes

laurenyu · 2019-12-10T22:19:42Z

README.rst

+
+Amazon SageMaker Autopilot is an automated machine learning (commonly referred to as AutoML) solution for tabular
+datasets. It automatically trains and tunes the best machine learning models for classification or regression based
+on your data, and host a serials of models on an Inference Pipeline.


s/host/hosts

s/serials/series

laurenyu · 2019-12-10T22:20:27Z

src/sagemaker/automl/README.rst

+Amazon SageMaker Autopilot is an automated machine learning (commonly referred to as AutoML) solution for tabular
+datasets. It automatically trains and tunes the best machine learning models for classification or regression based
+on your data, and host a serials of models on an Inference Pipeline.


same two comments here

laurenyu · 2019-12-10T22:22:58Z

src/sagemaker/automl/README.rst

+The SageMaker ``AutoML`` class is similar to a SageMaker ``Estimator`` where you define the attributes of an AutoML
+job and feed input data to start the job.
+
+A simple use case of an ``AutoML`` object would be:


"Here's a simple example of using the AutoML object:"

this isn't really a use case as much as it is just usage

laurenyu · 2019-12-10T22:24:09Z

src/sagemaker/automl/README.rst

+    auto_ml.fit(inputs=inputs)
+
+
+The above code will start an AutoML job (data processing, training, tuning) and output a maximum of 500 candidates by


s/will start/starts

s/output/outputs

laurenyu · 2019-12-10T22:29:44Z

src/sagemaker/automl/README.rst

+default. You can modify the number of output candidates by specifying ``max_candidates`` in the constructor. The AutoML
+job will figure out the problem type (BinaryClassification, MulticlassClassification, Regression), but you can also
+specify the problem type by setting ``problem_type`` in the constructor. Other configurable settings include security
+settings, time limits, job objectives, tags, etc.


can we link to ReadTheDocs so people know where to find the rest of the parameters?

I couldn't find the ReadTheDocs link for the AutoML class. For all new classes, only Analytics is there: https://sagemaker.readthedocs.io/en/stable/analytics.html

yeah they have to be added - I've got an open PR to do so: #1161 (won't block this PR on that one, but it'd be nice to follow up on it after)

laurenyu · 2019-12-10T22:30:35Z

src/sagemaker/automl/README.rst

+
+After an AutoML job is done, there are a few things that you can do with the result.
+
+1. Describe the AutoML job: ``describe_auto_ml_job()`` will give you an overview of the AutoML job, information


(optional) in RST, you can use #. to have the numbering done automatically

laurenyu · 2019-12-10T22:31:12Z

src/sagemaker/automl/README.rst

+SageMaker CandidateEstimator Class
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+The SageMaker ``CandidateEstimator`` class convert a dictionary with AutoML candidate information to an object that


s/convert/converts

laurenyu · 2019-12-10T22:32:39Z

src/sagemaker/automl/README.rst

+The SageMaker ``CandidateEstimator`` class convert a dictionary with AutoML candidate information to an object that
+allows you to re-run the candidate's step jobs.
+
+The simplest re-run would be feeding a new dataset but re-use all other configurations that the candidate used to have:


s/would be feeding/is to feed

s/re-use/reuse

s/ that the candidate used to have/from the candidate

laurenyu · 2019-12-10T22:32:56Z

src/sagemaker/automl/README.rst

+    candidate_estimator.fit(inputs=inputs)
+
+If you want to have more control over the step jobs of the candidate, you can call ``get_steps()`` and construct
+training/tunning jobs by yourself.


s/tunning/tuning

sagemaker-bot · 2019-12-12T18:57:34Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-12T19:13:22Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-12T19:20:26Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

laurenyu · 2019-12-12T21:32:51Z

src/sagemaker/automl/README.rst

+The SageMaker ``AutoML`` class is similar to a SageMaker ``Estimator`` where you define the attributes of an AutoML
+job and feed input data to start the job.
+
+Here's a simple example of using the AutoML ``object``:


nit: the backticks should go around "AutoML" not "object"

laurenyu · 2019-12-12T21:33:41Z

src/sagemaker/automl/README.rst

+default. You can modify the number of output candidates by specifying ``max_candidates`` in the constructor. The AutoML
+job will figure out the problem type (BinaryClassification, MulticlassClassification, Regression), but you can also
+specify the problem type by setting ``problem_type`` in the constructor. Other configurable settings include security
+settings, time limits, job objectives, tags, etc.


yeah they have to be added - I've got an open PR to do so: #1161 (won't block this PR on that one, but it'd be nice to follow up on it after)

sagemaker-bot · 2019-12-12T22:16:32Z

AWS CodeBuild CI Report

Result: FAILED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-13T19:28:53Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-13T19:43:12Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-13T19:53:05Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-13T20:56:04Z

AWS CodeBuild CI Report

Result: FAILED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-13T22:43:56Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-13T22:58:10Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-13T23:07:34Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-14T03:13:32Z

AWS CodeBuild CI Report

Result: FAILED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-16T17:37:17Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-16T17:50:16Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-16T18:00:59Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sagemaker-bot · 2019-12-16T18:31:44Z

AWS CodeBuild CI Report

Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

chuyang-deng and others added 6 commits December 5, 2019 14:58

fix: update with aws:master

4836fc9

update with aws:master

update with aws:master

bb12ba4

update with aws:master

skip auto ml canary tests if region is not us-east-2

8da106e

doc: AutoML README

06f6340

skip automl tests in non supported regions

ee1eb79

fix black format

f695ed1

laurenyu reviewed Dec 10, 2019

View reviewed changes

address comments

46954ea

laurenyu reviewed Dec 12, 2019

View reviewed changes

link readthedocs

ff1451f

laurenyu approved these changes Dec 13, 2019

View reviewed changes

Merge branch 'master' into auto_ml_integ

08a8271

Merge branch 'master' into auto_ml_integ

cd9a6f6

laurenyu merged commit 3b4ba23 into aws:master Dec 16, 2019

		auto_ml.fit(inputs=inputs)


		The above code will start an AutoML job (data processing, training, tuning) and output a maximum of 500 candidates by


		After an AutoML job is done, there are a few things that you can do with the result.

		1. Describe the AutoML job: ``describe_auto_ml_job()`` will give you an overview of the AutoML job, information

doc: AutoML #1158

doc: AutoML #1158

Uh oh!

Conversation

chuyang-deng commented Dec 10, 2019

Merge Checklist

Uh oh!

sagemaker-bot commented Dec 10, 2019

AWS CodeBuild CI Report

Uh oh!

sagemaker-bot commented Dec 10, 2019

AWS CodeBuild CI Report

Uh oh!

sagemaker-bot commented Dec 10, 2019

AWS CodeBuild CI Report

Uh oh!

sagemaker-bot commented Dec 10, 2019

AWS CodeBuild CI Report

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

sagemaker-bot commented Dec 12, 2019

AWS CodeBuild CI Report

Uh oh!

sagemaker-bot commented Dec 12, 2019

AWS CodeBuild CI Report

Uh oh!

sagemaker-bot commented Dec 12, 2019

AWS CodeBuild CI Report

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

sagemaker-bot commented Dec 12, 2019

AWS CodeBuild CI Report

Uh oh!

sagemaker-bot commented Dec 13, 2019

AWS CodeBuild CI Report

Uh oh!

sagemaker-bot commented Dec 13, 2019

AWS CodeBuild CI Report

Uh oh!

sagemaker-bot commented Dec 13, 2019