Free HP HPE2-N69 Practice Exam with Questions & Answers | Set: 2

This is done by running the model through a training loop, where the model is fed data and the parameter weights are adjusted based on the results of the model's performance on the data. For example, if the model is a neural network, the weights of the connections between the neurons are adjusted based on the results of the model's performance on the data. This process is repeated until the model performs better on the data, at which point the model is considered trained.

HPE Machine Learning Development Environment uses Amazon S3 to store checkpoints. To find the location of the best checkpoint created during an experiment, you need to look for a "determined-checkpoint/" bucket within Amazon S3, referencing your experiment ID. This bucket will contain all of the checkpoints that were created during the experiment.