Skip to content

01 Build and Deploy Site #59

01 Build and Deploy Site

01 Build and Deploy Site #59

Triggered via schedule November 12, 2024 01:09
Status Success
Total duration 1m 1s
Artifacts

sandpaper-main.yaml

on: schedule
Build Full Site
53s
Build Full Site
Fit to window
Zoom out
Zoom in

Annotations

4 warnings
Build Full Site
The following actions use a deprecated Node.js version and will be forced to run on node20: actions/checkout@v3. For more info: https://github.blog/changelog/2024-03-07-github-actions-all-actions-will-run-on-node20-instead-of-node16-by-default/
Build Full Site: episodes/04-ml-1.md#L45
[missing file]: [Artificial Intelligence (AI) is the broader concept of machines being able to carry out tasks in a way that we would consider "smart". Machine Learning (ML) is a subset of AI that involves training algorithms to learn from and make predictions based on data.](../fig/ml-vs-ai.png) [image missing alt-text]: ../fig/ml-vs-ai.png
Build Full Site: episodes/04-ml-1.md#L74
[missing file]: [Supervised learning involves training a model on labeled data, where the input comes with corresponding output labels, allowing the model to learn the relationship between inputs and outputs. In contrast, unsupervised learning works with unlabeled data, identifying patterns and structures within the data without predefined labels, often used for clustering and association tasks.](../fig/s-vs-us.png) [image missing alt-text]: ../fig/s-vs-us.png
Build Full Site: episodes/04-ml-1.md#L95
[missing file]: [Confusion metrics, also known as a confusion matrix, is a table used to evaluate the performance of a classification model. It displays the true positives, true negatives, false positives, and false negatives, providing insight into the accuracy, precision, recall, and overall effectiveness of the model's predictions.](../fig/metrics.png) [image missing alt-text]: ../fig/metrics.png