modify file paths for windows

ch02/ch02.py

@@ -2,6 +2,7 @@
 
 
 import numpy as np
+import os
 import pandas as pd
 import matplotlib.pyplot as plt
 from matplotlib.colors import ListedColormap
@@ -22,7 +23,15 @@
 
 
 
-# *The use of `watermark` is optional. You can install this IPython extension via "`pip install watermark`". For more information, please see: https://github.com/rasbt/watermark.*
+# *The use of `watermark` is optional. You can install this Jupyter extension via*  
+# 
+#     conda install watermark -c conda-forge  
+# 
+# or  
+# 
+#     pip install watermark   
+# 
+# *For more information, please see: https://github.com/rasbt/watermark.*
 
 # ### Overview
 # 
@@ -158,10 +167,15 @@ def predict(self, X):
 
 
 
-df = pd.read_csv('https://archive.ics.uci.edu/ml/'
-        'machine-learning-databases/iris/iris.data',
+
+s = os.path.join('https://archive.ics.uci.edu', 'ml',
+                 'machine-learning-databases', 'iris','iris.data')
+print('URL:', s)
+
+df = pd.read_csv(s,
                  header=None,
                  encoding='utf-8')
+
 df.tail()
 
 

ch12/ch12.py

@@ -124,7 +124,7 @@
 else:
     writemode = 'w'
 
-zipped_mnist = [f for f in os.listdir('./') if f.endswith('ubyte.gz')]
+zipped_mnist = [f for f in os.listdir() if f.endswith('ubyte.gz')]
 for z in zipped_mnist:
     with gzip.GzipFile(z, mode='rb') as decompressed, open(z[:-3], writemode) as outfile:
         outfile.write(decompressed.read()) 
@@ -561,6 +561,7 @@ def fit(self, X_train, y_train, X_valid, y_valid):
 
 
 
+
 plt.plot(range(nn.epochs), nn.eval_['cost'])
 plt.ylabel('Cost')
 plt.xlabel('Epochs')