first yadll commit

README.rst

@@ -86,7 +86,7 @@ Example
 
 Different networks tested on mnist:
 
-* Linear Regression
+* logisitic Regression
 * Multi Layer Perceptron
 * MLP with dropout
 * MLP with dropconnect
@@ -99,7 +99,6 @@ Different networks tested on mnist:
 * Stacked Denoising Autoencoder
 * Restricted Boltzmann Machine
 * Deep Belief Network
-* Convolutional Network
 * RNN
 * LSTM
 

setup.py

@@ -3,7 +3,7 @@
 
 setup(name="yadll",
       version="0.0.1",
-      description="Yet Another Deep Learning Lab. ultra light DL framework based on Theano",
+      description="Yet Another Deep Learning Lab. Ultra light Deep Learning framework based on Theano",
       author="Philippe Chavanne",
       author_email="philippe.chavanne@gmail.com",
       url="https://github.com/pchavanne/yadll",

yadll/hyperparameters.py

@@ -9,20 +9,24 @@ class Hyperparameters(object):
 
     Parameters
     ----------
-    name : `string`
+    name : `string`, {'batch_size', 'n_epochs', 'learning_rate', 'l1_reg', 'l2_reg', 'patience'}
         The name of the hyperparameter.
-        expected hyperparameters: {'batch_size', 'n_epochs', 'learning_rate', 'l1_reg', 'l2_reg', 'patience'}
     value : `float`
         The default value of the hyperparameter.
     range : `list` of `float`
-        A list of values itterated over during the gris search
+        A list of values iterated over during the gris search
 
     Examples
     --------
+    Define the hyperparameters of the model:
     >>> hp = Hyperparameters()   # Create an Hyperparameters instance
     >>> hp('batch_size', 500)    # Define an hyperparameter with its default value
     >>> hp('n_epochs', 1000, [10, 100, 1000, 1000])    # and range for the grid search
 
+    Grid search on the hyperparameters space:
+    >>> for param in hp:
+    >>>     # Do something with this set of hyperparameters
+
     """
     def __init__(self):
         self.hp_value = dict()