update readme with correct name, remove tensorflow import along and run output for each cell
@@ -23,5 +23,5 @@ The following summarizes each notebook for Sentence Similarity. Each notebook pr
|[Creating a Baseline model](baseline_deep_dive.ipynb)| Yes| A baseline model is a basic solution that serves as a point of reference for comparing other models to. The baseline model's performance gives us an indication of how much better our models can perform relative to a naive approach.|
|Senteval |[local](senteval_local.ipynb), [AzureML](senteval_azureml.ipynb)|SentEval is a widely used benchmarking tool for evaluating general-purpose sentence embeddings. Running SentEval locally is easy, but not necessarily efficient depending on the model specs. We provide an example on how to do this efficiently in Azure Machine Learning Service. |
|[GenSen on AzureML](gensen_aml_deep_dive.ipynb)| No | This notebook serves as an introduction to an end-to-end NLP solution for sentence similarity building one of the State of the Art models, GenSen, on the AzureML platform. We show the advantages of AzureML when training large NLP models with GPU.
-|[Automated Machine Learning(AutoML) with Deployment on Azure Container Instance](automl_local_deployment_ACI.ipynb)| Yes |This notebook shows users how to use AutoML on local machine and deploy the model as a webservice to Azure Container Instance(ACI) to get a sentence similarity score.
-|[Google Universal Sentence Encoder with Azure Machine Learning Pipeline, AutoML with Deployment on Azure Kubernetes Service](aml_pipelines_deployment_AKS.ipynb)| No | This notebook shows a user how to use AzureML pipelines and deploy the pipeline output model as a webservice to Azure Kubernetes Service which can be used as an end point to get sentence similarity scores.
+|[Automated Machine Learning(AutoML) with Deployment on Azure Container Instance](automl_local_deployment_aci.ipynb)| Yes |This notebook shows users how to use AutoML on local machine and deploy the model as a webservice to Azure Container Instance(ACI) to get a sentence similarity score.
+|[Google Universal Sentence Encoder with Azure Machine Learning Pipeline, AutoML with Deployment on Azure Kubernetes Service](automl_with_pipelines_deployment_aks.ipynb)| No | This notebook shows a user how to use AzureML pipelines and deploy the pipeline output model as a webservice to Azure Kubernetes Service which can be used as an end point to get sentence similarity scores.
