Readme

Overview

This repo contains notebooks and datasets used by the Analytics discipline to demonstrate how to implement anomaly detection.

Environment Set up

You can run the noteboos in your own local environment by following the steps below.

Install Python

You can download the latest version of Python from: https://www.python.org/downloads/

Install VS Code

You can download VS Code from: https://code.visualstudio.com/download

Install Python Extension for VS Code

1. Open VS Code Extensions toolbar

2. Find and install Python Extension for VS Code from Microsoft

   

Create your local virtual environment

1. Open the VS Code terminal

2. Install python package venv which enables the creation of local environments

   pip install venv

3. Create the local environment in your VS Code subfolder

   python -m venv .venv

Activate local virtual environment in Jupyter notebook

1. Open jupyter notebook
2. Connect jupyter notbook to local virtual environment

Activate local virtual environment in VS Code

1. In Visual Studio code launch the Command Pallette: Ctrl + Shift + P

   

2. Select Python: Select Interpreter

3. Select your local environment

   

4. Confirm that VS Code is pointing to your local virtual environment

   At the bottom right hand corner of VS Code, you should see your local virtual envrionment.

   

Activate virtual environement in the terminal

1. Open the terminal window inside VS Code

2. Run activate script file

   .venv\scripts\activate

3. Confirm you can see the environment name at the left of the command prompt

Install Python dependencies

The dependencies needed to run the notebooks are included in the requirements.txt file. You can install them all with the command:

pip install -r requirements.txt