mACHINE lEARNING eXPERIMENTS by LP SANSHODHANA

Author:LP, SANSHODHANA
Language: eng
Format: epub
Published: 2016-12-27T16:00:00+00:00

# Launch the graph

with tf.Session() as sess:

sess.run(init)

i=0

# Fit all training data

for epoch in range(training_epochs):

i=0

for (x, y) in zip(train_X, train_Y):

if i<2:

sess.run(optimizer, feed_dict={X: x, Y: y})

i=i+1

# Display logs per epoch step

if (epoch+1) % display_step == 0:

c = sess.run(cost, feed_dict={X: train_X, Y:train_Y})

print("Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(c), \

"W=", sess.run(W), "b=", sess.run(b))

print("Optimization Finished!")

training_cost = sess.run(cost, feed_dict={X: train_X, Y: train_Y})

print("Training cost=", training_cost, "W=", sess.run(W), "b=", sess.run(b), '\n')

The figure below shows the problem space and the regression line in the second scatter graph in the figure below.

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