Examples for Neptune.
To run the following examples you need to have Neptune CLI installed.
The goal of this example is to create a simple parameterizable job
that generates sine and cosine as functions of time (in seconds),
with the provided amplitude and sampling_rate.
The full description of the example can be found in the
documentation.
neptune run main.py --config config.yaml --dump-dir-url my_dump_dir
This example is an adaptation of source code from the deep learning Keras library which shows utilization of Neptune features. The example consists of a single Python file and uses Keras to train and evaluate a convolutional neural network that recognizes handwritten digits. Full description of the example can be found in the documentation.
neptune run mnist_cnn_neptune.py --config config.yaml --dump-dir-url mnist_cnn_neptune_output -- --kernel_size 5
This example is an adaptation of Linear Regression example from the scikit-learn machine learning library which shows utilization of Neptune features. The example consists of a single Python file using scikit-learn to train and evaluate a simple linear regression model that predicts disease progression of diabetes patients. The full description of the example can be found in the documentation.
neptune run plot_ols_neptune.py --config config.yaml --dump-dir-url plot_ols_neptune_output -- --feature_index 2