IN-PERSON - "Random Forests for Spatial Analyses" and "Polars or Pandas"

This meetup will be in-person at Amazon Web Services level 30, 300 George St, Brisbane City.

Please bring your own laptop if you would like to follow along.
There will be two topics.

5:15 - Doors open. Pizza arrives between 5:15 and 5:30. People who are new to Python can turn up at 5:15pm and we will provide individual assistance on how to install Python on your computer, though we will be using Google colab which does not require Python installed on your computer.

5:30 - Official start time. Pizza should have arrived and you will have some time to network with other pythonistas.

5:45 - Annie will present the first topic on Random Forests

In this beginner-friendly workshop, we'll use the Melbourne House Prices dataset to demonstrate how location and other property features affect house values as an example of how to use a machine learning method for spatial analysis in Python.

What You’ll Learn:

• Basics of Random Forest models for prediction
• Variable Importance in spatial data analysis
• Fine-tuning techniques with Grid Search and OOB error
• Practical skills in Python for data preparation, modelling, and visualisation

No prior machine learning experience is necessary—just bring your curiosity and enthusiasm for learning data analysis!

6:30 - Tim will present the second topic: Polars and Pandas - two DataFrame libraries. Which one is best for you?

A Google colab notebook will be provided so you can follow along https://colab.research.google.com/drive/1jAG4QzzLHInMQrmiVfcR5j24HXj42xC1

Beginners' Python and Machine Learning (BPAML) will only use your email address to contact you regarding your registration at this event. Your email address will be given to Amazon Web Services and is subject to their privacy policy. Amazon will only use provided email address as a unique identifier for attendees over all their events.

There is a slackspace for sharing data and chatting during the streaming event at beginnerspython.slack.com - please email skypyprojectatgmaildotcom for an invitation