What is a test data set?
A test data set, in the context of machine learning, is a subset of data that is used to evaluate the performance of a trained machine learning model. It is distinct from the training data set, which is used to train the model. The purpose of the test data set is to assess how well
- Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Introduction, What is machine learning
How do we compare the groups identified by the k-means algorithm with the "survived" column?
To compare the groups identified by the k-means algorithm with the "survived" column in the Titanic dataset, we need to evaluate the correspondence between the clustering results and the actual survival status of the passengers. This can be done by calculating various performance metrics, such as accuracy, precision, recall, and F1-score. These metrics provide insights
- Published in Artificial Intelligence, EITC/AI/MLP Machine Learning with Python, Clustering, k-means and mean shift, K means with titanic dataset, Examination review
What information is logged for each request made to the API in the Cloud Endpoints quickstart tutorial?
In the Cloud Endpoints quickstart tutorial, several pieces of information are logged for each request made to the API. These logs provide valuable insights into the usage and performance of the API, allowing developers to monitor and troubleshoot their applications effectively. Let's explore the information that is logged for each request in detail. 1. Request
What is the role of evaluation data in measuring the performance of a machine learning model?
Evaluation data plays a crucial role in measuring the performance of a machine learning model. It provides valuable insights into how well the model is performing and helps in assessing its effectiveness in solving the given problem. In the context of Google Cloud Machine Learning and Google tools for Machine Learning, evaluation data serves as