Finding Insights from Email - First Steps

The code samples here are the ones walked through in the talk Using AI to automatically find insights in email: A rapid prototyping story

To set up a SageMaker Notebook

Open the Amazon SageMaker console at https://console.aws.amazon.com/sagemaker/.

Choose Notebook instances, then choose Create notebook instance.

On the Create notebook instance page, provide the following information (if a field is not mentioned, leave the default values):

For Notebook instance name, type a name for your notebook instance.
For Instance type, choose ml.t2.medium. This is the least expensive instance type that notebook instances support.
For IAM role, choose Create a new role, then choose Create role.

Choose Create notebook instance.

In a few minutes, Amazon SageMaker launches an ML compute instance — in this case, a notebook instance — and attaches an ML storage volume to it. The notebook instance has a preconfigured Jupyter notebook server and a set of Anaconda libraries.

NOTE: You are charged while your SageMaker Notebook Instance is running. Make sure to familarise yourself with the pricing and always remember to Stop your Instance when you aren't using it. https://aws.amazon.com/sagemaker/pricing/

Updating your IAM Role

From the Notebook instance page click on the IAM role ARN hyperlink in the Permissions and encryption section. This should open the Summary page for that IAM Role. From here use the Attach policies button to add in permissions for Comprehend and Lex.

Copying the Juypter Notebooks to your SageMaker Instance

Once your instance is running choose "Open Jupyter". From here you have two options:

Use the Upload button to manually copy up the Jupyter Notebooks (.ipynb) files (make sure to include the data and img folders too)

or 2. Use the New button to open a terminal window and run the following commands to navigate to the correct location and clone this repo:

cd SageMaker

git clone https://github.com/virtualgill/intelligent-email-insights-first-steps

Adding in the Lex Bot

Navigate to the Lex Console at https://console.aws.amazon.com/lex

Choose Actions -> Import

Upload analyse_date_phrases_Export.json.zip included in this repo

Select the Bot and click navigate to the Editor page

Select "Build"

Once built choose "Publish" and choose an alias of "demo" (you can select a different name, but be sure to update any notebooks that use this bot too)