Azure Notebooks

1. Introduction

Jupyter Notebooks running R, Python, F#, online. Create an account, a project and a notebook to load data, generate a ML model, and deploy it as a web service.

Tip: Look at these examples.

2. Installation

1. Login or create an account.

2. Create a new project.

3. Create a new Python notebook.

3. Accessing Data

The methods presented in Azure Notebook include:

1. Use curl to retrieve a file from GitHub

2. Use a REST API to retrieve online data

3. Query an Azure SQL database

4. Access Azure Table Storage

5. Access Azure Blobs

   Share access to Azure Storage through Shared Access Signatures

Tip: bonus Azure databases.

3.1 Downloading File

Download a file using curl:

!curl https://raw.githubusercontent.com/petroleum101/figures/db46e7f48b8aab67a0dfe31696f6071fb7a84f1e/oil_price/oil_price.csv -o ../oil_price_temp.csv

Read in the data using pandas:

import pandas
dataframe_file = pandas.read_csv('../oil_price_temp.csv')
dataframe_file.head()

3.2 Http Requests

3.3 Azure SQL Databases

3.4 Azure Table Storage

3.5 Azure Blobs

4. Running ML Models

5. Deploy Web Service