tensorflow2.py

import numpy as np
import tensorflow as tf

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

w = tf.Variable(0, dtype = tf.float32) # initializing the parameter as 0.
x = tf.placeholder(tf.float32, [3, 1]) # defining x as a 3x1 column vector
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)

for i in range(1000):
    session.run(train, feed_dict = {x : coefficients})

print(session.run(w))