Merge pull request #1 from ericmand/patch-1

Fixed a single character typo in README.md

README.md

@@ -13,7 +13,7 @@ Here are some unique distinguishing features of Lambdo:
 
 * **No difference between features and models.** Lambdo unifies feature engineering and machine learning so that a workflow involves many feature definitions and many machine learning algorithms. It is especially important for deep learning where abstract intermediate features have to be learned.
 * **One workflow for both prediction and training.** Lambdo nodes combine applying a transformation with training its model so that nodes of a workflow can be re-trained when required. This also guarantees that the same features will be used for both learning phase and prediction phase.
-* **Columns first.**] Lambdo workflow use column operations along with table operations which makes many operations much simpler.
+* **Columns first.** Lambdo workflow use column operations along with table operations which makes many operations much simpler.
 * **User-defined functions for extensibility.** Lambdo relies on user-defined functions which can be as simple as format conversion and as complex as deep neural networks.
 * **Analysis of time-series and forecasting made easy.** Lambdo makes time series analysis much simpler by providing many using mechanisms like column families (for example, several moving averages with different window sizes), window-awareness (generation of windows is a built-in function), pre-defined functions for extracting goals.
 * **As flexible as programming and as easy as IDE.** Lambdo is positioned between (Python) programming and interactive environments (like KNIME)