The simplest least squares with TensorFlow

least_squares_1.py

import tensorflow as tf

x = tf.placeholder(tf.float32, [None, 1])
y_ = tf.placeholder(tf.float32, [None, 1])

b = tf.Variable(tf.zeros([1]))
w = tf.Variable(tf.zeros([1, 1]))

y = w * x + b

loss = tf.reduce_sum((y - y_) * (y - y_))
train_step = tf.train.GradientDescentOptimizer(0.005).minimize(loss)

sess = tf.Session()
sess.run(tf.initialize_all_variables())

for step in range(10):
    sess.run(train_step, feed_dict={x:[[2.3],[1.7],[-3.8],[0.5],[-4.1],[-1.5],[-2.5],[6.2]],
                                    y_:[[-4.4],[-3.6],[7.7],[-0.9],[8.3],[2.9],[4.9],[-12.2]]})
    print step, sess.run(w), sess.run(b)

Dear Tomonari Masada,

I tried to run it in JupyterLab Notebook, but error to print:

print step, sess.run(w), sess.run(b).

The error code is:
Cell In [1], line 35
print step, sess.run(w), sess.run(b)
^
SyntaxError: invalid syntax.

Please advise.
Thanks.
Hoe Min

Rewrite as 'print(step, sess.run(w), sess.run(b))'.
But this code was written many years ago. Other lines do not work for the current version of TensorFlow. Please google similar codes.