Unsupervised Machine Learning

Transcript

1. Unsupervised Machine Learning @bethanyjep
2. Requirements - Basic understanding of python - Jupyter Notebook installed in Visual Studio Code
3. Recap: what is machine learning? This is often the foundation for an AI system and is the way we "teach" a computer model to make prediction and draw conclusions from data. Machine learning automates the process of pattern-discovery by finding meaningful insights from real-world or generated data.
4. Steps in Machine Learning Understand the problem Collect and Prepare data Choose a training method Train your model Evaluate the model Parameter tuning Predict
5. What is unsupervised machine learning? Finding patterns in data without labels.
6. Clustering • Clustering is a machine learning task where it looks to find objects that resemble one another and group these into groups called clusters. • Clustering algorithms are used to process raw, unclassified data objects into groups represented by structures or patterns in the information.
7. K-Means Clustering • Silhouette scoring: evaluate the quality of clusters created using clustering algorithms • Elbow method: a heuristic used in determining the number of clusters in a data set • Inertia: a measure of how internally coherent clusters are • Variance: the average of the squared differences from the Mean
8. Let's get coding!!!