exercises instructions

Author: ogrisel

tutorial/exercises.rst

@@ -1,4 +1,55 @@
 Exercises
 =========
 
+To do the exercises, copy the content of the 'skeletons' folder as
+a new folder named 'workspaces'.
+
+Then fire an ipython shell and run the work-in-progress script with::
+
+  >>> %run workspace/exercise_XX_script.py arg1 arg2 arg3
+
+If an exception is triggered, use the ``%debug`` to fire-up a post
+mortem ipdb session.
+
+Refine the implementation and iterate until the exercise is solved.
+
+
+Exercise 1: Sentiment Analysis on movie reviews
+-----------------------------------------------
+
+- Write a text classification pipeline to classify movie reviews as either
+  positive or negative.
+
+- Find a good set of parameters using grid search.
+
+- Evaluate the performance on a held out test set.
+
+
+Exercise 2: Language identification
+-----------------------------------
+
+- Write a text classification pipeline using a custom preprocessor and
+  CharNGramAnalyzer using data from Wikipedia articles as training set.
+
+- Evaluate the performance on some held out test set.
+
+
+Exercise 3: CLI text classification utility
+-------------------------------------------
+
+Using the results of the previous exercises and the ``cPickle``
+module of the standard library, write a command line utility that
+detect the language of some text provided on ``stdin`` and estimate
+the polarity (positive or negative) if the text is written in
+English.
+
+Bonus point if the utility is able to give a confidence level for its
+predictions.
+
+
+Exercise 4: Face recognition
+----------------------------
+
+Build a classifier that recognize person on faces pictures from the
+Labeled Faces in the Wild dataset.