Deep Learning Essentials

Deep Learning Essentials:

This page will become a reference page of most common used libraries when doing deep learning research in python.


Numpy

np.random
np.random.permutation
np.array([123.68, 116.779, 103.939], dtype=np.float32).reshape((3,1,1))

np.argmax(all_preds, axis=1)
np.array(preds)
np.newaxis
np.zeros

Scipy

from scipy import misc, ndimage

from scipy.ndimage.interpolation import zoom
from scipy.ndimage import imread

csv

with open('results.csv', 'wb') as csv_file:

writer = csv.writer(csv_file)

        writer.writerow

        for result in results:

            for key, value in result.items():

               writer.writerow([key, value])

Keras

from keras.preprocessing import image
image.load_img

Linear Model - Dense Layer (Fully Connexted: ax+b)