Krunal Kapadiya krunal3kapadiya

## tf_step_by_step_1.py
# Set model weights
W = tf.Variable(rng.randn(), name="weight")
b = tf.Variable(rng.randn(), name="bias")

## tf_step_by_step_1.py
# tf Graph Input
X = tf.placeholder("float")
Y = tf.placeholder("float")

## tf_step_by_step_1_n_sample
n_samples = train_X.shape[0]

## tf_step_by_step_1_data.py
train_X = numpy.asarray([3.3,4.4,5.5,6.71,6.93,4.168,9.779,6.182,7.59,2.167,
                         7.042,10.791,5.313,7.997,5.654,9.27,3.1])
train_Y = numpy.asarray([1.7,2.76,2.09,3.19,1.694,1.573,3.366,2.596,2.53,1.221,
                         2.827,3.465,1.65,2.904,2.42,2.94,1.3])

## tf_step_by_step_1_import_variables_epochs.py
learning_rate = 0.01
training_epochs = 1000
display_step = 50

## tf_step_by_step_1_import_rng.py
rng = numpy.random

## tf_step_by_step_1_import_lib.py
from __future__ import print_function
import tensorflow as tf
import numpy
import matplotlib.pyplot as plt

## tensorflow_version.py
import tensorflow as tf;
print(tf.__version__)

## matrix.py
from __future__ import print_function

import tensorflow as tf

# Create a Constant op that produces a 1x2 matrix.  The op is
# added as a node to the default graph.

matrix1 = tf.constant([[3., 3.]])

# Create another Constant that produces a 2x1 matrix.

## basic_operations_in_session.py
from __future__ import print_function

import tensorflow as tf

a = tf.placeholder(tf.int32)
b = tf.placeholder(tf.int32)

# Define some operations
add = tf.add(a, b)
sub = tf.subtract(a, b)
	# Set model weights
	W = tf.Variable(rng.randn(), name="weight")
	b = tf.Variable(rng.randn(), name="bias")
	# tf Graph Input
	X = tf.placeholder("float")
	Y = tf.placeholder("float")
	train_X = numpy.asarray([3.3,4.4,5.5,6.71,6.93,4.168,9.779,6.182,7.59,2.167,
	7.042,10.791,5.313,7.997,5.654,9.27,3.1])
	train_Y = numpy.asarray([1.7,2.76,2.09,3.19,1.694,1.573,3.366,2.596,2.53,1.221,
	2.827,3.465,1.65,2.904,2.42,2.94,1.3])
	from __future__ import print_function
	import tensorflow as tf
	import numpy
	import matplotlib.pyplot as plt
	from __future__ import print_function

	import tensorflow as tf

	# Create a Constant op that produces a 1x2 matrix. The op is
	# added as a node to the default graph.

	matrix1 = tf.constant([[3., 3.]])

	# Create another Constant that produces a 2x1 matrix.
	from __future__ import print_function

	import tensorflow as tf

	a = tf.placeholder(tf.int32)
	b = tf.placeholder(tf.int32)

	# Define some operations
	add = tf.add(a, b)
	sub = tf.subtract(a, b)