From ae03b9380042e2602ff4144161444d65386c0db2 Mon Sep 17 00:00:00 2001 From: Heather Shapiro Date: Tue, 17 Sep 2019 13:36:14 -0400 Subject: [PATCH] added pixelserver to azureml notebooks --- examples/README.md | 9 ++++++++- examples/entailment/entailment_xnli_bert_azureml.ipynb | 7 +++++++ examples/question_answering/bidaf_aml_deep_dive.ipynb | 7 +++++++ .../pretrained-BERT-SQuAD-deep-dive-aml.ipynb | 7 +++++++ .../question_answering_system_bidaf_quickstart.ipynb | 7 +++++++ .../automl_local_deployment_aci.ipynb | 7 +++++++ .../automl_with_pipelines_deployment_aks.ipynb | 7 +++++++ examples/sentence_similarity/bert_senteval.ipynb | 7 +++++++ examples/sentence_similarity/gensen_aml_deep_dive.ipynb | 7 +++++++ examples/text_classification/tc_bert_azureml.ipynb | 7 +++++++ 10 files changed, 71 insertions(+), 1 deletion(-) diff --git a/examples/README.md b/examples/README.md index 4edd96c1a..2046febfe 100644 --- a/examples/README.md +++ b/examples/README.md @@ -2,7 +2,6 @@ This folder contains examples and best practices, written in Jupyter notebooks, for building Natural Language Processing systems for the following scenarios. - |Category|Applications|Methods|Languages| |---| ------------------------ | ------------------- |---| |[Text Classification](text_classification)|Topic Classification|BERT, XLNet|en, hi, ar| @@ -14,3 +13,11 @@ This folder contains examples and best practices, written in Jupyter notebooks, |[Annotation](annotation)|Text Annotation|Doccano|| |[Model Explainability](model_explainability)|DNN Layer Explanation|DUUDNM (Guan et al.)| +## Data/Telemetry +The Azure Machine Learning notebooks collect browser usage data and send it to Microsoft to help improve our products and services. Read Microsoft's [privacy statement to learn more](https://privacy.microsoft.com/en-US/privacystatement). + +To opt out of tracking, please go to the raw `.ipynb` files and remove the following line of code (the URL will be slightly different depending on the file): + +```sh + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/text_classification/tc_bert_azureml.png)" +``` \ No newline at end of file diff --git a/examples/entailment/entailment_xnli_bert_azureml.ipynb b/examples/entailment/entailment_xnli_bert_azureml.ipynb index 3598ea926..af049f3cc 100644 --- a/examples/entailment/entailment_xnli_bert_azureml.ipynb +++ b/examples/entailment/entailment_xnli_bert_azureml.ipynb @@ -14,6 +14,13 @@ "\n", "**Note: To learn how to do pre-training on your own, please reference the [AzureML-BERT repo](https://github.com/microsoft/AzureML-BERT) created by Microsoft.**" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/entailment/entailment_xnli_bert_azureml.png)" + ] }, { "cell_type": "code", diff --git a/examples/question_answering/bidaf_aml_deep_dive.ipynb b/examples/question_answering/bidaf_aml_deep_dive.ipynb index de13e4f8c..cf75d5de4 100644 --- a/examples/question_answering/bidaf_aml_deep_dive.ipynb +++ b/examples/question_answering/bidaf_aml_deep_dive.ipynb @@ -15,6 +15,13 @@ "source": [ "# BiDAF Model Deep Dive on AzureML" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/question_answering/bidaf_aml_deep_dive.png)" + ] }, { "cell_type": "markdown", diff --git a/examples/question_answering/pretrained-BERT-SQuAD-deep-dive-aml.ipynb b/examples/question_answering/pretrained-BERT-SQuAD-deep-dive-aml.ipynb index 093735442..fdc089119 100644 --- a/examples/question_answering/pretrained-BERT-SQuAD-deep-dive-aml.ipynb +++ b/examples/question_answering/pretrained-BERT-SQuAD-deep-dive-aml.ipynb @@ -16,6 +16,13 @@ "# Question Answering: Fine-Tune BERT on AzureML (PyTorch)\n", "**BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding** [\\[1\\]](#References)" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/question_answering/pretrained_BERT_SQuAD_deep_dive_aml.png)" + ] }, { "cell_type": "markdown", diff --git a/examples/question_answering/question_answering_system_bidaf_quickstart.ipynb b/examples/question_answering/question_answering_system_bidaf_quickstart.ipynb index 17812006c..b3ed49196 100644 --- a/examples/question_answering/question_answering_system_bidaf_quickstart.ipynb +++ b/examples/question_answering/question_answering_system_bidaf_quickstart.ipynb @@ -15,6 +15,13 @@ "), [BiDAF](https://www.semanticscholar.org/paper/Bidirectional-Attention-Flow-for-Machine-Seo-Kembhavi/007ab5528b3bd310a80d553cccad4b78dc496b02\n", "), using Azure Container Instances ([ACI](https://azure.microsoft.com/en-us/services/container-instances/))." ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/question_answering/bidaf_quickstart.png)" + ] }, { "cell_type": "markdown", diff --git a/examples/sentence_similarity/automl_local_deployment_aci.ipynb b/examples/sentence_similarity/automl_local_deployment_aci.ipynb index fd1b25b8d..b67c9b55d 100644 --- a/examples/sentence_similarity/automl_local_deployment_aci.ipynb +++ b/examples/sentence_similarity/automl_local_deployment_aci.ipynb @@ -15,6 +15,13 @@ "source": [ "# Local Automated Machine Learning Model with ACI Deployment for Predicting Sentence Similarity" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/sentence_similarity/automl_local_deployment_aci.png)" + ] }, { "cell_type": "markdown", diff --git a/examples/sentence_similarity/automl_with_pipelines_deployment_aks.ipynb b/examples/sentence_similarity/automl_with_pipelines_deployment_aks.ipynb index ed0826af5..42d85e42a 100644 --- a/examples/sentence_similarity/automl_with_pipelines_deployment_aks.ipynb +++ b/examples/sentence_similarity/automl_with_pipelines_deployment_aks.ipynb @@ -15,6 +15,13 @@ "source": [ "# AzureML Pipeline, AutoML, AKS Deployment for Sentence Similarity" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/sentence_similarity/automl_with_pipelines_deployment_aks.png)" + ] }, { "cell_type": "markdown", diff --git a/examples/sentence_similarity/bert_senteval.ipynb b/examples/sentence_similarity/bert_senteval.ipynb index c8d6c9996..c423aa715 100644 --- a/examples/sentence_similarity/bert_senteval.ipynb +++ b/examples/sentence_similarity/bert_senteval.ipynb @@ -6,6 +6,13 @@ "source": [ "# Parallel Experimentation with BERT on AzureML" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/sentence_similarity/bert_senteval.png)" + ] }, { "cell_type": "markdown", diff --git a/examples/sentence_similarity/gensen_aml_deep_dive.ipynb b/examples/sentence_similarity/gensen_aml_deep_dive.ipynb index 00f48a85d..23c4a0e05 100644 --- a/examples/sentence_similarity/gensen_aml_deep_dive.ipynb +++ b/examples/sentence_similarity/gensen_aml_deep_dive.ipynb @@ -16,6 +16,13 @@ "# Training GenSen on AzureML with SNLI Dataset\n", "**GenSen: Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning** [\\[1\\]](#References)" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/sentence_similarity/gensen_aml_deep_dive.png)" + ] }, { "cell_type": "markdown", diff --git a/examples/text_classification/tc_bert_azureml.ipynb b/examples/text_classification/tc_bert_azureml.ipynb index f5cfdc5ee..3e6e4aca3 100644 --- a/examples/text_classification/tc_bert_azureml.ipynb +++ b/examples/text_classification/tc_bert_azureml.ipynb @@ -11,6 +11,13 @@ "# Text Classification of MultiNLI Sentences using BERT with Azure ML Pipelines" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/nlp/examples/text_classification/tc_bert_azureml.png)" + ] + }, { "cell_type": "markdown", "metadata": {},