Merge pull request #333 from pycom/pb-ml-integration

sintaxe fixes on ml documentation

Author: alipsilv

content/pybytes/mlintegration/features.md

@@ -90,7 +90,7 @@ Select the devices and click on the **DEPLOY MODEL** button.
 
 ![Model Deployment](/gitbook/assets/pybytes/ml/deploy.png)
 
-* Once the model is deployed on the device, it can be called from python code to classify new gestures using the data collected from the accelerometer sensor. 
+* Once the model is deployed on the device, it can be called from python code to classify new gestures using the data collected from the accelerometer sensor.
 
 * The path to the deployed model is: `flash/model_definition.json`. This file is going to be used by the device firmware, and once generated it should not be changed by the user. Any changes can cause features to malfunction.
 
@@ -102,13 +102,13 @@ from math import sin
 import json
 import pycom
 
-# This is just a dummy example. In a real application, the input 
+# This is just a dummy example. In a real application, the input
 # data should be collected from the accelerometer.
 
 def new_model(model_str):
  """Instantiate deployed model."""
  return pycom.ml_new_model(model_str)
- 
+
 
 def run_model(window_data):
  """Run model to classify data."""
@@ -119,14 +119,14 @@ def run_model(window_data):
  print(' {}: {:.2}%'.format(label, result[index] * 100))
 
 # Read deployed model.
-with open('flash/model_definition.json') as file:
+with open('/flash/model_definition.json') as file:
 
  # Parse the model_definition.
  model_str = file.read()
  model_dict = json.loads(model_str)
 
  # Read blocks.
- for block in model_dict['model']['blocks']:
+ for block in model_dict['blocks']:
  if block['block_type'] == 'pre_processing_block':
  pp_block = block
  if block['block_type'] == 'nn_block':