Write minimal instructions for reproduction

Author: chrlen

README.md

@@ -1,6 +1,18 @@
-Implement latetent dirichlet allocation.
+# Latent Dirichlet Allocation
+
+Implement variational inference algorithm for latent dirichlet allocation.
 Train model on a small subset of wikipedia.
+Evaluate and visualize with pyLDAvis
+
+To reproduce check the following scripts:
+- scripts/setup_anaconda_env.bash to build suitable anaconda-environment.
+- scripts/00_setup.bash to download the wikipedia dataset.
+- scripts/extractSmallSubset.bash to extract a subset of the dataset.
+- scripts/01_preprocess.bash to process xml files and save the dictionary and wordcounts for each document.
+- scripts/02_training.bash to estimate the distribution parameters and save the
+- to visualize run the jupyter-notebook with the same name and point it to the location of your trained model (by setting the path in the second cell). A Small model is in
 
-Questions:
-- is english ok?
-- gsm.parsing.preprocessing.preprocess_string does all at once, ok?
+There are three relevant Python classes in the package **lda**.
+- Dataset in lda/dataset.py for all corpus preprocessing operations as well as loading and saving datasets in the native Python serialization format pickle.
+- LDA in lda/inference.py to perform the inference algorithm on a dataset
+- GenMod in lda/generativeModel.py to sample from a LDA model given the hyperparameters