# HG changeset patch
# User Jeff Hammel <k0scist@gmail.com>
# Date 1504556951 25200
# Node ID e2dd9503098f7c1b1f2e56d2c2c98aef734d54d7
# Parent  0f29b02f4806f374deeee792c43e071d125e9210
finalize logistic regression notes

diff -r 0f29b02f4806 -r e2dd9503098f links.txt
--- a/links.txt	Mon Sep 04 13:20:25 2017 -0700
+++ b/links.txt	Mon Sep 04 13:29:11 2017 -0700
@@ -1,1 +1,2 @@
 https://s3.amazonaws.com/MLMastery/ml_performance_improvement_cheatsheet.pdf?__s=2gnd4eijcmfwyncxqmmz
+http://www.wildml.com/2015/09/implementing-a-neural-network-from-scratch/
diff -r 0f29b02f4806 -r e2dd9503098f tvii/logistic_regression.py
--- a/tvii/logistic_regression.py	Mon Sep 04 13:20:25 2017 -0700
+++ b/tvii/logistic_regression.py	Mon Sep 04 13:29:11 2017 -0700
@@ -185,8 +185,8 @@
     """
 
     # initialize parameters with zeros
-    raise NotImplementedError('TODO') # -> record TODO items
-    w, b = initialize_with_zeros(X_train.shape[0])
+    w = np.zeros((X_train.shape[0], 1))
+    b = 0
 
     # Gradient descent
     parameters, grads, costs = optimize(w, b, X_train, Y_train, num_iterations, learning_rate, print_cost=print_cost)