Merge pull request #15 from 0xflotus/master

docs: fixed small error

README.md

@@ -60,7 +60,7 @@ In the above example, the line graph is used as the default visualization. Howev
 One of the significant strengths of TensorWatch is the ability to combine, compose, and create custom visualizations effortlessly. For example, you can choose to visualize an arbitrary number of streams in the same plot. Or you can visualize the same stream in many different plots *simultaneously*. Or you can place an arbitrary set of visualizations side-by-side. You can even create your own custom visualization widget simply by creating a new Python class, implementing a few methods.
 
 ## Comparing Results of Multiple Runs
-Each TensorWatch stream may contain a metric of your choice. By default, TensorWatch saves all streams in a single file, but you could also choose to save each stream in seprate files or not to save them at all (for example, sending streams over sockets or into the console directly, zero hit to disk!). Later you can open these streams and direct them to one or more visualizations. This design allows you to quickly compare the results from your different experiments in your choice of visualizations easily. 
+Each TensorWatch stream may contain a metric of your choice. By default, TensorWatch saves all streams in a single file, but you could also choose to save each stream in separate files or not to save them at all (for example, sending streams over sockets or into the console directly, zero hit to disk!). Later you can open these streams and direct them to one or more visualizations. This design allows you to quickly compare the results from your different experiments in your choice of visualizations easily. 
 
 ## Training within Jupyter Notebook
 Often you might prefer to do data analysis, ML training, and testing - all from within Jupyter Notebook instead of from a separate script. TensorWatch can help you do sophisticated, real-time visualizations effortlessly from code that is run within a Jupyter Notebook end-to-end.