fix: TrainStream, CrossValidate, and Typescript

Overhauled the internals of TrainStream and CrossValidate so they are decoupled from the networks themselves, as well as being able to restore or store CrossValidate from json.

Added examples for CrossValidate and TrainStream, and as well one for learning math, to test the typescript type file.

Too I added missing typescript configs and examples.

*

README.md

@@ -28,6 +28,8 @@
       + [For training with `RNN`, `LSTM` and `GRU`](#for-training-with-rnn-lstm-and-gru)
     + [Training Options](#training-options)
     + [Async Training](#async-training)
+    + [Cross Validation](#cross-validation)
+    + [Train Stream](#train-stream)
 - [Methods](#methods)
     + [train](#train)
 - [Failing](#failing)
@@ -274,6 +276,49 @@ With multiple networks you can train in parallel like this:
     .catch(handleError);
 ```
 
+### Cross Validation
+[Cross Validation](https://en.wikipedia.org/wiki/Cross-validation_(statistics)) can provide a less fragile way of training on larger data sets.  The brain.js api provides Cross Validation in this example:
+```js
+const crossValidate = new CrossValidate(brain.NeuralNetwork);
+const stats = crossValidate.train(data, networkOptions, trainingOptions, k); //note k (or KFolds) is optional
+const net = crossValidate.toNetwork();
+
+
+// optionally later
+const json = crossValidate.toJSON();
+const net = crossValidate.fromJSON(json);
+```
+
+An example of using cross validate can be found in [examples/cross-validate.js](examples/cross-validate.js)
+
+### Train Stream
+Streams are a very powerful tool in node for massive data spread across processes and are provided via the brain.js api in the following way: 
+```js
+const net = new brain.NeuralNetwork();
+const trainStream = new brain.TrainStream({
+  neuralNetwork: net,
+  floodCallback: function() {
+    flood(trainStream, data);
+  },
+  doneTrainingCallback: function(stats) {
+    // network is done training!  What next?
+  }
+});
+
+// kick it off
+readInputs(trainStream, data);
+
+function readInputs(stream, data) {
+  for (let i = 0; i < data.length; i++) {
+    stream.write(data[i]);
+  }
+  // let it know we've reached the end of the inputs
+  stream.endInputs();
+}
+```
+
+An example of using train stream can be found in [examples/stream-example.js](examples/stream-example.js)
+
 # Methods
 ### train
 The output of `train()` is a hash of information about how the training went:
@@ -341,7 +386,7 @@ The network now has a [WriteStream](http://nodejs.org/api/stream.html#stream_cla
 
 
 ### Example
-Refer to [`stream-example.js`](./examples/cli/stream-example.js) for an example on how to train the network with a stream.
+Refer to [`stream-example.js`](examples/stream-example.js) for an example on how to train the network with a stream.
 
 
 ### Initialization