import neptune

neptune.init(api_token='ANONYMOUS',
             project_qualified_name='shared/scikit-optimize-integration')

## Step 2: Create an Experiment

neptune.create_experiment(name='skopt-sweep')

## Step 3: Run skopt with the Neptune Callback

# Create Neptune Callback
import neptunecontrib.monitoring.skopt as skopt_utils

neptune_callback = skopt_utils.NeptuneCallback()

# Run the skopt minimize function with the Neptune Callback
results = skopt.forest_minimize(objective,
                                space,
                                n_calls=25,
                                n_random_starts=10,
                                callback=[neptune_callback])

## Step 4: Log best parameter configuration, best score and diagnostic plots

skopt_utils.log_results(results)

## Step 5: Stop logging and Explore results in the Neptune UI

# tests
Example #2
0
neptune.init(api_token='ANONYMOUS',
             project_qualified_name='shared/scikit-optimize-integration')

# Quickstart

## Step 1: Create an Experiment

neptune.create_experiment(name='skopt-sweep')

## Step 2: Run skopt with the Neptune Callback

# Create Neptune Callback
import neptunecontrib.monitoring.skopt as skopt_utils

neptune_callback = skopt_utils.NeptuneCallback()

# Run the skopt minimize function with the Neptune Callback
results = skopt.forest_minimize(objective,
                                space,
                                n_calls=25,
                                n_random_starts=10,
                                callback=[neptune_callback])

## Step 3: Log best parameter configuration, best score and diagnostic plots

skopt_utils.log_results(results)

## Step 4: Stop logging and Explore results in the Neptune UI

neptune.stop()