2017년 9월 22일 K-ICT 빅데이터센터 딥러닝 교육 자료 #2 TensorFlow & Deep Learning

3. import tensorflow as tf
a = tf.constant(1)
b = tf.constant(1)
c = a + b
session = tf.Session()
session.run(c)

4. import tensorflow as tf
a = tf.constant(1)
b = tf.constant(1)
c = a + b
session = tf.Session()
session.run(c)

5. import tensorflow as tf
a = tf.constant(1)
b = tf.constant(1)
c = a + b
session = tf.Session()
session.run(c)

34. A(m×n) * B(n×q) = C(_×_)

35. A(m×n) * B(n×q) = C(m×q)

36. A(3×2) * B(_×_) = C(3×1)

37. A(3×2) * B(2×1) = C(3×1)

40. A(3×2) * B(_×_) = C(1×2)

41. A(_×_) * B(3×2) = C(1×2)

42. A(1×3) * B(3×2) = C(1×2)

45. import tensorflow as tf
x = tf.constant(
[
[100, 100],
[80, 20],
[50, 40]
]
)
x

46. w = tf.constant(
[
[1],
[1.5]
]
)
y = tf.matmul(x, w)
session = tf.Session()
session.run(y)

50. tf.reset_default_graph()
a = tf.placeholder(tf.float32, name='a')
b = tf.placeholder(tf.float32, name='b')
c = tf.add(a, b, name='c')
d = tf.multiply(a, b, name='d')
e = tf.subtract(c, d, name='e')
session = tf.Session()
tf.summary.FileWriter('summary', session.graph)

52. tensorboard
--logdir=summary
--reload-interval=1

58. session.run(e, feed_dict={
a: 1,
b: 2
})

59. x = tf.placeholder(tf.float32, [None, 2])
w = tf.constant([[1], [1.5]])
y = tf.matmul(x, w)
x_data = np.array(
[
[100, 100],
[80, 20],
[50, 40]
]
)
session = tf.Session()
session.run(y, feed_dict={
x: x_data
})

60. x = tf.placeholder(tf.float32, [None, 2])
w = tf.constant([[1], [1.5]])
y = tf.matmul(x, w)
x_data = np.array(
[
[100, 100],
[80, 20],
[50, 40]
]
)
session = tf.Session()
session.run(y, feed_dict={
x: x_data
})

61. x_data = np.array(
[
[100, 100],
[80, 20],
[50, 40],
[78, 82],
[90, 95],
[24, 74],
[0, 10],
[98, 40]
]
)
session.run(y, feed_dict={
x: x_data
})