ahn-github
diff --git a/‎lab-04-3-file_input_linear_regression.py‎
Lines changed: 38 additions & 0 deletions b/‎lab-04-3-file_input_linear_regression.py‎
Lines changed: 38 additions & 0 deletions
diff --git a/‎…multi_variable_linear_regression_feed.py‎ ‎…multi_variable_linear_regression_feed.py‎lab-04-3-multi_variable_linear_regression_feed.py renamed to lab-04-4-multi_variable_linear_regression_feed.py b/‎…multi_variable_linear_regression_feed.py‎ ‎…multi_variable_linear_regression_feed.py‎lab-04-3-multi_variable_linear_regression_feed.py renamed to lab-04-4-multi_variable_linear_regression_feed.py
@@ -0,0 +1,38 @@
+# Lab 4 Multi-variable linear regression
+import tensorflow as tf
+import numpy as np
+
+xy = np.loadtxt('data.csv', delimiter=',', dtype=np.float32)
+x_data = xy[:, 0:-1]
+y_data = xy[:, [-1]]
+
+print(x_data.shape, x_data, len(x_data))
+print(y_data.shape, y_data)
+
+W = tf.Variable(tf.random_uniform(
+    shape=[3, 1], minval=-1.0, maxval=1.0, dtype=tf.float32))
+b = tf.Variable(tf.random_uniform(
+    shape=[1], minval=-1.0, maxval=1.0, dtype=tf.float32))
+
+# Hypothesis
+hypothesis = tf.matmul(x_data, W) + b
+
+# Simplified cost function
+cost = tf.reduce_mean(tf.square(hypothesis - y_data))
+
+# Minimize
+optimizer = tf.train.GradientDescentOptimizer(learning_rate=0.01)
+train = optimizer.minimize(cost)
+
+# Initialize variables
+init = tf.global_variables_initializer()
+
+# Launch graph
+sess = tf.Session()
+sess.run(init)
+
+for step in range(2001):
+    sess.run(train)
+    if step % 20 == 0:
+        print(step, sess.run(cost),
+              sess.run(hypothesis), sess.run(W), sess.run(b))