README.md in vowpalwabbit-0.1.0 vs README.md in vowpalwabbit-0.1.1

@@ -2,13 +2,15 @@
 
 [Vowpal Wabbit](https://vowpalwabbit.org) - fast online machine learning - for Ruby
 
 :fire: Uses the C API for blazing performance
 
+[![Build Status](https://travis-ci.org/ankane/vowpalwabbit.svg?branch=master)](https://travis-ci.org/ankane/vowpalwabbit)
+
 ## Installation
 
-First, [install Vowpal Wabbit](https://vowpalwabbit.org/start.html). For Homebrew, use:
+First, install the [Vowpal Wabbit C++ library](https://vowpalwabbit.org/start.html). For Homebrew, use:
 
 ```sh
 brew install vowpal-wabbit
 ```
 
@@ -28,11 +30,11 @@
 ```
 
 Train a model
 
 ```ruby
-model = VowpalWabbit::Regressor.new(l: 100)
+model = VowpalWabbit::Regressor.new(learning_rate: 100)
 model.fit(x, y)
 ```
 
 Use `VowpalWabbit::Classifier` for classification and `VowpalWabbit::Model` for other models
 
@@ -89,10 +91,16 @@
 
 ```ruby
 [[1, 2, 3], [4, 5, 6]]
 ```
 
+Or a Numo NArray
+
+```ruby
+Numo::DFloat.new(3, 2).seq
+```
+
 Or an array of strings
 
 ```ruby
 [
   "0 | price:.23 sqft:.25 age:.05 2006",
@@ -103,11 +111,18 @@
 
 Or a path to a file
 
 ```ruby
 model.fit("train.txt")
+model.partial_fit("train.txt")
 model.predict("train.txt")
 model.score("train.txt")
+```
+
+Files can be compressed
+
+```ruby
+model.fit("train.txt.gz")
 ```
 
 Read more about the [input format](https://github.com/VowpalWabbit/vowpal_wabbit/wiki/Input-format)
 
 ## History