http://machinelearning.{region}.amazonaws.com/#X-Amz-Target=AmazonML_20141212.Predict<p>Generates a prediction for the observation using the specified <code>ML Model</code>.</p> <p> <b>Note:</b> Not all response parameters will be populated. Whether a response parameter is populated depends on the type of model requested.</p>
{
"success": true,
"data": {
"id": "abc123",
"created_at": "2025-01-01T00:00:00Z"
}
}{
"success": false,
"error": {
"code": "VALIDATION_ERROR",
"message": "Invalid request parameters"
}
}1curl --request POST \2 --url 'http://machinelearning.{region}.amazonaws.com/#X-Amz-Target=AmazonML_20141212.Predict' \3 --header 'accept: application/json' \4 --header 'content-type: application/json'1{2 "success": true,3 "data": {4 "id": "abc123",5 "created_at": "2025-01-01T00:00:00Z"6 }7}http://machinelearning.{region}.amazonaws.com/#X-Amz-Target=AmazonML_20141212.Predict<p>Generates a prediction for the observation using the specified <code>ML Model</code>.</p> <p> <b>Note:</b> Not all response parameters will be populated. Whether a response parameter is populated depends on the type of model requested.</p>
{
"success": true,
"data": {
"id": "abc123",
"created_at": "2025-01-01T00:00:00Z"
}
}{
"success": false,
"error": {
"code": "VALIDATION_ERROR",
"message": "Invalid request parameters"
}
}1curl --request POST \2 --url 'http://machinelearning.{region}.amazonaws.com/#X-Amz-Target=AmazonML_20141212.Predict' \3 --header 'accept: application/json' \4 --header 'content-type: application/json'1{2 "success": true,3 "data": {4 "id": "abc123",5 "created_at": "2025-01-01T00:00:00Z"6 }7}