From c387c4fd0d2cfbce13626e8825373ab2a17de759 Mon Sep 17 00:00:00 2001
From: Paul Cheuk <puzert@gmail.com>
Date: Sun, 23 Aug 2015 17:20:38 +0800
Subject: [PATCH] add my code

---
 mine_code/logistic_regression.py |  1 +
 mine_code/theano_intro.py        | 11 +++++
 mine_code/theano_intro_2.py      | 76 ++++++++++++++++++++++++++++++++
 3 files changed, 88 insertions(+)
 create mode 100644 mine_code/logistic_regression.py
 create mode 100644 mine_code/theano_intro.py
 create mode 100644 mine_code/theano_intro_2.py

diff --git a/mine_code/logistic_regression.py b/mine_code/logistic_regression.py
new file mode 100644
index 00000000..1e352899
--- /dev/null
+++ b/mine_code/logistic_regression.py
@@ -0,0 +1 @@
+logistic_regression.py
\ No newline at end of file
diff --git a/mine_code/theano_intro.py b/mine_code/theano_intro.py
new file mode 100644
index 00000000..311451bd
--- /dev/null
+++ b/mine_code/theano_intro.py
@@ -0,0 +1,11 @@
+import theano
+from theano import tensor as T
+
+a=T.scalar()
+b=T.scalar()
+y=a*b
+
+multiply = theano.function(inputs=[a, b], outputs=y)
+
+print multiply(3, 4)
+print multiply(4, 33)
\ No newline at end of file
diff --git a/mine_code/theano_intro_2.py b/mine_code/theano_intro_2.py
new file mode 100644
index 00000000..8db47031
--- /dev/null
+++ b/mine_code/theano_intro_2.py
@@ -0,0 +1,76 @@
+import theano
+from theano import tensor as T
+import numpy as np
+
+
+trX = np.linspace(1, 1, 101)
+trY= 2* trX * np.random.randn(*trX.shape)*0.33
+
+X= T.scalar()
+Y = T.scalar()
+
+def model(X, w):
+	return X*w
+
+
+w = theano.shared(np.asarray(0, dtype=theano.config.floatX))
+
+y = model(X, w)
+
+
+cost = T.mean(T.sqr(y-Y))
+
+gradient = T.grad(cost=cost, wrt=w)
+
+updates = [[w, w- gradient*0.01]]
+
+train = theano.function(inputs=[X, Y], outputs=cost, updates=updates, allow_input_downcast=True)
+
+
+for i in range(100):
+	for x, y in zip(trX, trY):
+		train(x, y)
+
+
+print w
+
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