Moss

.circleci/config.yml

@@ -3,7 +3,7 @@ jobs:
   test_regression_model:
     working_directory: ~/project
     docker:
-      - image: circleci/python:3.7.2
+      - image: circleci/python:3.8
     steps:
       - checkout
       - run:
@@ -20,7 +20,7 @@ jobs:
   test_ml_api:
     working_directory: ~/project
     docker:
-      - image: circleci/python:3.7.2
+      - image: circleci/python:3.8
     steps:
       - checkout
       - run:
@@ -35,7 +35,7 @@ jobs:
   train_and_upload_regression_model:
     working_directory: ~/project
     docker:
-      - image: circleci/python:3.7.2
+      - image: circleci/python:3.8
     steps:
       - checkout
       - run: 

README.md

@@ -1,2 +1,2 @@
 # Deploying Machine Learning Models
-For the documentation, visit the course on Udemy.
+For the documentation, visit the course on Udemy.

packages/ml_api/requirements.txt

@@ -1,7 +1,11 @@
 --extra-index-url=${PIP_EXTRA_INDEX_URL}
 
 # api
-flask==1.0.2
+flask==1.1.1
+jinja2==2.10.3
+markupsafe==1.1.1
+itsdangerous==1.1.0
+werkzeug==0.16.0
 
 # schema validation
 marshmallow==2.17.0

packages/ml_api/tests/test_controller.py

@@ -45,5 +45,5 @@ def test_prediction_endpoint_returns_prediction(flask_test_client):
     response_json = json.loads(response.data)
     prediction = response_json['predictions']
     response_version = response_json['version']
-    assert math.ceil(prediction[0]) == 112476
+    assert math.ceil(prediction[0]) == 112512
     assert response_version == _version

packages/regression_model/regression_model/processing/preprocessors.py

@@ -91,7 +91,7 @@ def fit(self, X, y=None):
 
         for var in self.variables:
             # the encoder will learn the most frequent categories
-            t = pd.Series(X[var].value_counts() / np.float(len(X)))
+            t = pd.Series(X[var].value_counts() / np.float64(len(X)))
             # frequent labels:
             self.encoder_dict_[var] = list(t[t >= self.tol].index)
 

packages/regression_model/requirements.txt

@@ -3,17 +3,17 @@
 # updates/fixes, whilst ensuring we don't install a major update which could introduce backwards incompatible changes.
 
 # Model Building Requirements
-numpy>=1.18.1,<1.19.0
-pandas>=0.25.3,<0.26.0
-scikit-learn>=0.22.1,<0.23.0
-joblib>=0.14.1,<0.15.0
+numpy>=1.18.1
+pandas>=0.25.3
+scikit-learn>=0.21.3
+joblib>=0.14.1
 
 # testing requirements
-pytest>=5.3.2,<6.0.0
+pytest>=5.3.2
 
 # packaging
-setuptools>=41.4.0,<42.0.0
-wheel>=0.33.6,<0.34.0
+setuptools>=41.4.0
+wheel>=0.33.6
 
 # fetching datasets
-kaggle>=1.5.6,<1.6.0
+kaggle>=1.5.6

packages/regression_model/tests/test_predict.py

@@ -15,7 +15,7 @@ def test_make_single_prediction():
     # Then
     assert subject is not None
     assert isinstance(subject.get('predictions')[0], float)
-    assert math.ceil(subject.get('predictions')[0]) == 112476
+    assert math.ceil(subject.get('predictions')[0]) == 112512
 
 
 def test_make_multiple_predictions():

scripts/fetch_kaggle_dataset.sh

@@ -1,3 +1,5 @@
 #!/usr/bin/env bash
 
-kaggle competitions download -c house-prices-advanced-regression-techniques -p packages/regression_model/regression_model/datasets/
+kaggle competitions download -c house-prices-advanced-regression-techniques -p packages/regression_model/regression_model/datasets/
+
+unzip packages/regression_model/regression_model/datasets/house-prices-advanced-regression-techniques.zip -d packages/regression_model/regression_model/datasets