Tensorflow 机器学习项目实战 记录

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Tensorflow 机器学习项目实战 记录

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基本操作

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简单矩阵运算

import tensorflow as tf
sess = tf.InteractiveSession()

x = tf.constant([[2, 5, 3, -5],
            [0, 3, -2, 5],
            [4, 3, 5, 3],
            [6, 1, 4, 0]])
y = tf.constant([[4, -7, 4, -3, 4],
            [6, 4, -7, 4, 7],
            [2, 3, 2, 1, 4],
            [1, 5, 5, 5, 2]])
floatx = tf.constant([[2., 5., 3., -5.],
                [0., 3., -2., 5.],
                [4., 3., 5., 3.],
                [6., 1., 4., 0.]])

  # 矩阵转置
tf.transpose(x).eval()  
array([[ 2,  0,  4,  6],
       [ 5,  3,  3,  1],
       [ 3, -2,  5,  4],
       [-5,  5,  3,  0]])

#矩阵相乘  Matrix Multiplication
tf.matmul(x, y).eval()
array([[ 2,  0,  4,  6],
       [ 5,  3,  3,  1],
       [ 3, -2,  5,  4],
       [-5,  5,  3,  0]])

#矩阵行列式（determinant）
tf.matrix_determinant(floatx).eval()
817.99969

#逆矩阵(inverse matrix)
tf.matrix_inverse(floatx).eval()
array([[-0.00855745,  0.10513447, -0.18948655,  0.29584354],
       [ 0.12958434,  0.12224938,  0.01222495, -0.05134475],
       [-0.01955992, -0.18826404,  0.28117359, -0.18092909],
       [-0.08557458,  0.05134474,  0.10513448, -0.0415648 ]], dtype=float32)

#行列式求解
tf.matrix_solve(floatx, [[1],[1],[1],[1]]).eval()
array([[ 0.202934  ],
       [ 0.21271393],
       [-0.10757945],
       [ 0.02933985]], dtype=float32)

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约简(reduction)

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x = tf.constant([[1, 2, 3],
                [3, 2, 1],
                [-1, -2, -3]])
boolean_tensor = tf.constant([[True, False, True],
                             [False, False, True],
                             [True, False, False]])

# 乘积方式降维，reduction_indices=1在