Pendahuluan TensorFlow di Python
Isaiah Hull
Visiting Associate Professor of Finance, BI Norwegian Business School
add(), multiply(), matmul(), dan reduce_sum()gradient(), reshape(), dan random()| Operation | Use |
|---|---|
gradient() |
Menghitung kemiringan fungsi pada suatu titik |
reshape() |
Mengubah bentuk tensor (mis. 10x10 menjadi 100x1) |
random() |
Mengisi tensor dengan nilai dari sebaran probabilitas |
Pada banyak masalah, kita ingin mencari optimum suatu fungsi.
Kita dapat melakukannya dengan gradient().


# Import tensorflow under the alias tf
import tensorflow as tf
# Define x
x = tf.Variable(-1.0)
# Define y within instance of GradientTape
with tf.GradientTape() as tape:
tape.watch(x)
y = tf.multiply(x, x)
# Evaluate the gradient of y at x = -1
g = tape.gradient(y, x)
print(g.numpy())
-2.0

# Import tensorflow as alias tf
import tensorflow as tf
# Generate grayscale image
gray = tf.random.uniform([2, 2], maxval=255, dtype='int32')
# Reshape grayscale image
gray = tf.reshape(gray, [2*2, 1])

# Import tensorflow as alias tf
import tensorflow as tf
# Generate color image
color = tf.random.uniform([2, 2, 3], maxval=255, dtype='int32')
# Reshape color image
color = tf.reshape(color, [2*2, 3])

Pendahuluan TensorFlow di Python