import numpy as np
import tensorflow as tf

coefficients = np.array([[1.], [-10.], [25.]])

w = tf.Variable(0,dtype=tf.float32)
x = tf.placeholder(tf.float32, [3,1])
# cost = tf.add(tf.add(w**2,tf.multiply(-10.,w)),25)
# cost = w**2 - 10*w + 25
cost = x[0][0]*w**2 + x[1][0]*w + x[2][0]
train = tf.train.GradientDescentOptimizer(0.01).minimize(cost)

init = tf.global_variables_initializer()
session = tf.Session()
session.run(init)
print(session.run(w))
#output: 0

session.run(train,feed_dict={x:coefficients})
print(session.run(w))
#output: 0.1

for i in range(1000):
    session.run(train,feed_dict={x:coefficients})
print(session.run(w))
#output: 4.99999