AmazonML Lab updated code

ml.py

import boto3
from boto3.session import Session

session = Session(aws_access_key_id='AWS_ACCESS_KEY_ID', aws_secret_access_key='AWS_SECRET_ACCESS_KEY')
machinelearning = session.client('machinelearning', region_name='us-east-1')
labels = {'1': 'walking', '2': 'walking upstairs', '3': 'walking downstairs', '4': 'sitting', '5': 'standing', '6': 'laying'}

# fill your model ID and Endpoint here!
model_id = 'MODEL_ID'
prediction_endpoint = 'MODEL_ENDPOINT'

def get_record(filename='record.csv'):
    record = {}
    with open(filename) as f:
        for index, val in enumerate(f.readline().split(',')):
            record['Var%03d' % (index + 1)] = val
    return record
   
try:
    response = machinelearning.predict(
        MLModelId=model_id,
        Record=get_record(),
        PredictEndpoint=prediction_endpoint,
    )
except Exception as e:
    print(e)
else:
    label = response['Prediction']['predictedLabel']
    print("You are currently %s." % labels[label])