In [1]:

    

import tensorflow as tf
var1 = tf.constant([1,2,3],dtype =tf.float32) # variable x
var2 = tf.constant([13,23,33],dtype =tf.float32) #variable y

m1 = tf.reduce_mean(var1) #mean(x)
m2 = tf.reduce_mean(var2) #mean(y)

sub=tf.subtract(var1,m1) #variance(x)
sq = tf.square(sub)
v = tf.reduce_sum(sq) 

c1 = tf.subtract(var1,m1)# c0-variance
c2=tf.subtract(var2,m2)
m=tf.multiply(c1,c2)
covariance=tf.reduce_sum(m)

mg=tf.div(covariance,v)# slope m

cp=tf.multiply(mg,m1)

cg=tf.subtract(m2,cp)#intercept c

with tf.Session() as sess:
    tf.InteractiveSession
    print(sess.run(var1))
    print(sess.run(var2))
    print(sess.run(m1))
    print(sess.run(m2))
    print(sess.run(v))
    print(sess.run(covariance))
    print(sess.run(mg))
    print(sess.run(cg))
    writer=tf.summary.FileWriter("/tmp/tboard/output_n",sess.graph)
    writer.close()


    

    




[ 1.  2.  3.]
[ 13.  23.  33.]
2.0
23.0
2.0
20.0
10.0
3.0

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