Knowing the version of Python and tensorflow currently installed on your PC is important as tensorflow may not run on the latest version of python, or you installed a 32-bit […]

The python with statement is a little strange to programmers of other languages. It is frequently occurred in tensorflow related codes like: with tf.Session() as sess: do something A new […]

The tensorflow.constant is one of the functions to create a tensor with known values. Its usage is flexible and may not be what you think. The simplest usage would be: […]

LTU(Linear Threshold Unit) \(\vec{w}=\{w_1,w_2,…,w_n\}\) is the weight vector, \(\vec{x}=\{x_1,x_2,…,x_n\}\) is an input feature vector. step(z) can be a heaviside step function which outputs 1 for z>=0, and outputs 0 for […]

To understand tensorflow computation graph, you need to know how to print or plot it. If you can visualize the computation graph, it would be easy to understand it. The […]

np.random.seed(4) m = 60 w1, w2 = 0.1, 0.3 noise = 0.1 angles = np.random.rand(m) * 3 * np.pi / 2 – 0.5 X = np.empty((m, 3)) X = np.empty((m, […]

import numpy as np X=2*np.random.rand(100,1) y=4+3*X+np.random.randn(100,1) X_b=np.c_[np.ones((100,1)),X]# add x0 = 1 to each instance theta_best=np.linalg.inv(X_b.T.dot(X_b)).dot(X_b.T).dot(y) numpy.rand(100,1) generates a 100*1 array, whose elements are random number ranging from 0 to 1. numpy.randn(100,1) generates a 100*1 array whose elements […]

We’ve learnt sklearn KFold. KFold splits an array into several groups. If the elements in the array are associated with a label/class, there would raise a problem. The ration of […]