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	foreach (var item in Model.Items)
	{
		PropertyDescriptorCollection properties = TypeDescriptor.GetProperties(item.DataItem);
		<ul>
		foreach (PropertyDescriptor property in properties)
		{
			<li>@property.Name</li>
		}
		</ul>
	}

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[INFO] No sources to compile
[INFO]
[INFO] --- maven-surefire-plugin:2.12.4:test (default-test) @ deeplearning4j-examples ---
[INFO] No tests to run.
[INFO]
[INFO] --- maven-jar-plugin:2.4:jar (default-jar) @ deeplearning4j-examples ---
[INFO] Building jar: /home/trevor.simonton/java/dl4j-0.4-examples/target/deeplearning4j-examples-0.4-rc0-SNAPSHOT.jar
[INFO]
[INFO] --- maven-shade-plugin:2.4.3:shade (default) @ deeplearning4j-examples ---
[INFO] Including org.deeplearning4j:deeplearning4j-nlp:jar:0.4-rc3.8 in the shaded jar.

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[INFO] Scanning for projects...
[INFO]                                                                         
[INFO] ------------------------------------------------------------------------
[INFO] Building DeepLearning4j Examples 0.4-rc0-SNAPSHOT
[INFO] ------------------------------------------------------------------------
[INFO] 
[INFO] --- maven-clean-plugin:2.5:clean (default-clean) @ deeplearning4j-examples ---
[INFO] 
[INFO] --- maven-resources-plugin:2.6:resources (default-resources) @ deeplearning4j-examples ---
[INFO] Using 'UTF-8' encoding to copy filtered resources.

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ListBuilder listBuilder = builder.list(2);

GravesLSTM.Builder hiddenLayerBuilder = new GravesLSTM.Builder();
hiddenLayerBuilder.nIn(100);
hiddenLayerBuilder.nOut(100);
hiddenLayerBuilder.activation("tanh");
listBuilder.layer(0, hiddenLayerBuilder.build());

RnnOutputLayer.Builder outputLayerBuilder = new RnnOutputLayer.Builder(LossFunction.MCXENT);
outputLayerBuilder.activation("softmax");

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 double foo[] = {0.07662966102361679,-0.15683715045452118,-0.09958696365356445,-0.5582161545753479,0.13371440768241882,0.145623579621315,0.21786752343177795,0.037577372044324875,0.010457501746714115,-0.01822548173367977,0.07133414596319199,0.10989873111248016,-0.004703379701822996,0.24611054360866547,0.1842348575592041,-0.03501710295677185,-0.28120318055152893,0.3167855143547058,-0.021439414471387863,-0.10285429656505585,0.31841185688972473,-0.047598835080862045,-0.4360429048538208,0.19820629060268402,0.02021874487400055,-0.3637917637825012,-0.19628046452999115,0.15301348268985748,-0.001860927906818688,-0.28961265087127686,-0.04005725681781769,-0.28192153573036194,0.12212064117193222,0.21076101064682007,0.006745698396116495,0.09953082352876663,-0.13900607824325562,-0.034233808517456055,0.10835923999547958,0.06281674653291702,0.04705433174967766,0.02800493873655796,-0.03654691204428673,0.0717429369688034,0.21126438677310944,0.061982423067092896,0.015610983595252037,0.18408675491809845,-0.020207442343235016,-0.

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<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>CS5800</groupId>
    <artifactId>Word2Vec</artifactId>
    <version>1.0-SNAPSHOT</version>
    <properties>

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import org.deeplearning4j.models.embeddings.loader.WordVectorSerializer;
import org.deeplearning4j.models.embeddings.wordvectors.WordVectors;
import org.nd4j.linalg.factory.Nd4j;
import java.io.FileNotFoundException;
import java.util.*;
import java.io.File;


public class TestWord2Vec {
    private WordVectors wordVectors;

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second 0.11818692833185196 -0.11586838960647583 0.003194663440808654 0.014543217606842518 0.12441886961460114 0.12494827806949615 -0.08607793599367142 0.1377992480993271 0.059452880173921585 0.11989010870456696 0.07708896696567535 -0.2107475847005844 0.05193556472659111 -0.11327853798866272 0.08074815571308136 0.08647062629461288 -0.11267949640750885 0.38330137729644775 0.05268869176506996 -0.20677907764911652 0.1454552710056305 0.04928664490580559 -0.12514610588550568 -0.1795852780342102 -0.07380848377943039 0.345684289932251 -0.12782983481884003 0.08223460614681244 -0.21559175848960876 0.06637492030858994 0.24465835094451904 -0.26894834637641907 -0.019167153164744377 -0.26744407415390015 0.22837163507938385 -0.2611274719238281 0.18729257583618164 0.14440852403640747 0.11006656289100647 -0.1000005379319191 -0.07726669311523438 0.09986642748117447 0.09000968933105469 0.03311610221862793 0.049440786242485046 -0.07943201065063477 0.20683448016643524 0.004119229968637228 -0.08807511627674103 -0.14113424718379974

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```
{
  "Exists": true,
  "Event": {
    "ID": "35",
    "Title": "QA Test Event",
    "Owner": "Paul Polelle",
    "City": "North Chicago",
    "State": "AL",
    "UpdateDate": 1472660819,

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