index.js

	// Train classifier
	console.log("Training...");
	let trainingIteration = await trainer.trainProject(project.id);

	console.log("Training started...");
	while (trainingIteration.status == "Training") {
		await setTimeoutPromise(1000, null);
		trainingIteration = await trainer.getIteration(project.id, trainingIteration.id)
	}
	console.log("Training status: " + trainingIteration.status);

	// Publish the iteration to endpoint
	await trainer.publishIteration(project.id, trainingIteration.id, publishIterationName, predictionResourceId);

	const predictor = new PredictionApiClient(predictionKey, endpoint);
	const testFile = fs.readFileSync(`${dataRoot}/test/maybe-pizza.jpeg`);

	const results = await predictor.classifyImage(project.id, publishIterationName, testFile);

	// Show results
	console.log("Results:");
	results.predictions.forEach(predictedResult => {
		console.log(`\t ${predictedResult.tagName}: ${(predictedResult.probability * 100.0).toFixed(2)}%`);
	});
})()