From d3dc35dbb65f3caba706a8ab24209226d0ff5006 Mon Sep 17 00:00:00 2001 From: Jeff Shepherd Date: Thu, 13 Jun 2019 11:03:25 -0700 Subject: [PATCH] Removed deprecated notebooks from readme --- .../automated-machine-learning/README.md | 19 ------------------- 1 file changed, 19 deletions(-) diff --git a/how-to-use-azureml/automated-machine-learning/README.md b/how-to-use-azureml/automated-machine-learning/README.md index dc667c8e..f6d3a5bd 100644 --- a/how-to-use-azureml/automated-machine-learning/README.md +++ b/how-to-use-azureml/automated-machine-learning/README.md @@ -115,15 +115,6 @@ jupyter notebook - Simple example of using automated ML for regression - Uses local compute for training -- [auto-ml-remote-execution.ipynb](remote-execution/auto-ml-remote-execution.ipynb) - - Dataset: scikit learn's [digit dataset](http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits) - - Example of using automated ML for classification using a remote linux DSVM for training - - Parallel execution of iterations - - Async tracking of progress - - Cancelling individual iterations or entire run - - Retrieving models for any iteration or logged metric - - Specify automated ML settings as kwargs - - [auto-ml-remote-amlcompute.ipynb](remote-batchai/auto-ml-remote-amlcompute.ipynb) - Dataset: scikit learn's [digit dataset](http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits) - Example of using automated ML for classification using remote AmlCompute for training @@ -133,12 +124,6 @@ jupyter notebook - Retrieving models for any iteration or logged metric - Specify automated ML settings as kwargs -- [auto-ml-remote-attach.ipynb](remote-attach/auto-ml-remote-attach.ipynb) - - Dataset: Scikit learn's [20newsgroup](http://scikit-learn.org/stable/datasets/twenty_newsgroups.html) - - handling text data with preprocess flag - - Reading data from a blob store for remote executions - - using pandas dataframes for reading data - - [auto-ml-missing-data-blacklist-early-termination.ipynb](missing-data-blacklist-early-termination/auto-ml-missing-data-blacklist-early-termination.ipynb) - Dataset: scikit learn's [digit dataset](http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits) - Blacklist certain pipelines @@ -156,10 +141,6 @@ jupyter notebook - Get details for a automated ML Run. (automated ML settings, run widget & all metrics) - Download fitted pipeline for any iteration -- [auto-ml-remote-execution-with-datastore.ipynb](remote-execution-with-datastore/auto-ml-remote-execution-with-datastore.ipynb) - - Dataset: Scikit learn's [20newsgroup](http://scikit-learn.org/stable/datasets/twenty_newsgroups.html) - - Download the data and store it in DataStore. - - [auto-ml-classification-with-deployment.ipynb](classification-with-deployment/auto-ml-classification-with-deployment.ipynb) - Dataset: scikit learn's [digit dataset](http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits) - Simple example of using automated ML for classification