1 lesson

Author: likefallwind

1 Neural Networks and Deep Learning/Week 2/Logistic Regression as a Neural Network/.ipynb_checkpoints/Logistic+Regression+with+a+Neural+Network+mindset+v5-checkpoint.ipynb

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+import numpy as np
+import h5py
+    
+    
+def load_dataset():
+    train_dataset = h5py.File('datasets/train_catvnoncat.h5', "r")
+    train_set_x_orig = np.array(train_dataset["train_set_x"][:]) # your train set features
+    train_set_y_orig = np.array(train_dataset["train_set_y"][:]) # your train set labels
+
+    test_dataset = h5py.File('datasets/test_catvnoncat.h5', "r")
+    test_set_x_orig = np.array(test_dataset["test_set_x"][:]) # your test set features
+    test_set_y_orig = np.array(test_dataset["test_set_y"][:]) # your test set labels
+
+    classes = np.array(test_dataset["list_classes"][:]) # the list of classes
+    
+    train_set_y_orig = train_set_y_orig.reshape((1, train_set_y_orig.shape[0]))
+    test_set_y_orig = test_set_y_orig.reshape((1, test_set_y_orig.shape[0]))
+    
+    return train_set_x_orig, train_set_y_orig, test_set_x_orig, test_set_y_orig, classes
+