Logistic Regression with a Neural Network mindset python example
print ("sigmoid([0, 2]) = " + str(sigmoid(np.array([0,2]))))Logistic Regression with a Neural Network mindset python example
print ("sigmoid([0, 2]) = " + str(sigmoid(np.array([0,2]))))Logistic Regression with a Neural Network mindset python example
- m_train (number of training examples)
- m_test (number of test examples)
- num_px (= height = width of a training image)Logistic Regression with a Neural Network mindset python example
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, classesLogistic Regression with a Neural Network mindset python example
train_set_x = train_set_x_flatten/255.
test_set_x = test_set_x_flatten/255.Logistic Regression with a Neural Network mindset python example
dim = 2
w, b = initialize_with_zeros(dim)
print ("w = " + str(w))
print ("b = " + str(b))Logistic Regression with a Neural Network mindset python example
sigmoid([0, 2]) = [ 0.5 0.88079708]Logistic Regression with a Neural Network mindset python example
X_flatten = X.reshape(X.shape[0], -1).T # X.T is the transpose of XLogistic Regression with a Neural Network mindset python example
- a training set of m_train images labeled as cat (y=1) or non-cat (y=0)
- a test set of m_test images labeled as cat or non-cat
- each image is of shape (num_px, num_px, 3) where 3 is for the 3 channels (RGB). Thus, each image is square (height = num_px) and (width = num_px).Logistic Regression with a Neural Network mindset python example
y = [1], it's a 'cat' picture.Logistic Regression with a Neural Network mindset python example
- Initialize the parameters of the model
- Learn the parameters for the model by minimizing the cost
- Use the learned parameters to make predictions (on the test set)
- Analyse the results and concludeCopyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
