ML tutorial: Clustering with K-means - Learn customer segmentation!

My name is Aurelie and I'm graduating with an MSc in Artificial Intelligence from the University of Limerick.

I run monthly machine learning and deep learning tutorials in Dublin with a small group of people.

**In this tutorial, we will explore unsupervised learning by training a clustering model using the K-means algorithm with Scikit-learn. We will work with a publicly available dataset though the exact dataset will be a surprise! Together, we will walk through the full pipeline from data preprocessing to model training and evaluation.

This tutorial will focus on customer segmentation using K-means clustering, a technique widely used across industries to better understand and group customers based on behaviours, preferences or demographics. Whether you are in retail, finance, healthcare or tech, customer segmentation is a key part of delivering targeted services and improving business outcomes.

The session is particularly relevant for professionals working in marketing, product development, sales, customer experience or data analysis but anyone curious about how machine learning can drive smarter business decisions is welcome!

The Jupyter notebook used during the tutorial will be shared with all participants. It includes the complete code from data preparation to model training and evaluation. It can be reused or adapted for your own business needs or personal projects.

• The tutorials are interactive and will be conducted using Jupyter notebooks on Google Colaboratory (a free, cloud-based platform that lets us write and run code directly in the browser). While Google Colaboratory is free to use, tasks that require more computational power (such as training deep learning models) may benefit from GPU access. In that case, Google offers a once-off payment for around €10 which can last several months depending on your usage.
  Some familiarity with Python or other programming languages is helpful but not required. Everyone is welcome to join and learn at their own pace.

• The tutorial lasts for 2 hours from 2.30 to 4.30 pm.

• During the tutorial, I share the Jupyter notebook with participants so they can keep it for future reference. We go through the notebook step by step together and I do my best to answer any questions along the way.

• We will be working with a variety of Python libraries including Scikit-learn, PyTorch, TensorFlow, Keras, Seaborn, Pandas and Matplotlib and the Hugging Face framework. These tools will help us explore different machine learning and deep learning techniques using publicly available datasets.

• Each tutorial focuses on a different algorithm in depth. Topics covered include linear regression, logistic regression, K-means clustering, decision trees, artificial neural networks (ANNs), convolutional neural networks (CNNs) for image classification, object detection and natural language processing. The goal is to break down each technique step by step, making it approachable and practical for real-world applications.

The tutorials take place at the Camdem court hotel in Dublin 2 at the bar (coffees need to be ordered at the restaurant). It will run from 2.30 to 4.30 pm.

Camdem court hotel
Camden Street Lower, Saint Kevin's, Dublin, D02 W086

• The tutorials are a high-level practical introduction to machine learning and deep learning and the emphasis on understanding how we process the data , train and evaluate a model with Python. We won't cover the mathematics behind it however some tutorials may have mathematical formulas as part of the algorithm explanation and some tutorials might have more complex data preprocessing as it depends on the datasets and the task we are doing. However the tutorials focus on the practical part!
• Payments need to be made in advance to secure your place and fees are non-refundable unless I need to cancel the event, in this case refunds will be made.