Supervised vs Unsupervised Learning

Overview

This is the repository done for the "Supervised vs Unsupervised Learning" talk for Quito's AI event in Impaqto.

This project was built with Kedro setup using the version kedro 0.19.5.

Take a look at the Kedro documentation to get started.

About my self.

I am Sebastián Sarasti. I have worked as data scientist and machine learning engineer for almost 3 years in the industry. Since 5 years ago, I got amazed by data science and AI world since 2019. From this point, I applied machine learning and data science for many of my projects in the academia.

You can know more about my self and what I do here: https://www.linkedin.com/in/sebastiansarasti/

Rules and guidelines

In order to get the best out of the template:

• Don't remove any lines from the .gitignore file we provide
• Make sure your results can be reproduced by following a data engineering convention
• Don't commit data to your repository
• Don't commit any credentials or your local configuration to your repository. Keep all your credentials and local configuration in conf/local/

How to install dependencies and run the files

Declare any dependencies in requirements.txt for pip installation.

To install them, run:

pip install -r requirements.txt

Then, you can run locally or in the cloud the notebook.

Project dependencies

To see and update the dependency requirements for your project use requirements.txt. Install the project requirements with pip install -r requirements.txt.

Further information about project dependencies

How to work with Kedro and notebooks

Note: Using kedro jupyter or kedro ipython to run your notebook provides these variables in scope: catalog, context, pipelines and session.

Jupyter, JupyterLab, and IPython are already included in the project requirements by default, so once you have run pip install -r requirements.txt you will not need to take any extra steps before you use them.