<NME> README.md
<BEF> Pyramid Machine Learning Library

## **Requirements**
If you just want to use pyramid as a command line tool, all you need is [Java 8](http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html).
## **Requirements**
If you just want to use pyramid as a command line tool (which is very simple), all you need is [Java 8](http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html).

If you are also a Java developer and wish to call Pyramid Java APIs, you will also need [Maven](https://maven.apache.org/).

## **Setup**
Pyramid doesn't require any installation effort. All you need is downloading the latest [pre-compiled package](https://github.com/cheng-li/pyramid/releases) (with a name like pyramid-x.x.x.zip) and decompressing it. Now you can move into the created folder and type 

`./pyramid config/welcome.properties`

You will see a welcome message and that means everything is working perfectly.

Windows users please see the [notes](https://github.com/cheng-li/pyramid/wiki/Notes-for-Windows-Users).
## **Command Line Usage**
All algorithms/functions implemented in Pyramid can be run though a simple command, with the following syntax:

`./pyramid <properties_file>`

Example: 

`./pyramid config/welcome.properties`

or

`./pyramid config/cbm.properties`

Pyramid uses [Maven](https://maven.apache.org/) for its build system.

To compile and package the project, simply run the `mvn clean package -DskipTests` command in the cloned directory. The compressed package will be created under the target/releases directory. Just decompress either the .zip file or the .tar.gz file and you are done.
_If you are a Java developer who prefer working with the source code or want to contribute to the Pyramid package:_

Pyramid uses [Maven](https://maven.apache.org/) for its build system.

To compile and package the project from the source code, simply run the `mvn clean package -DskipTests` command in the cloned directory. The compressed package will be created under the core/target/releases directory.

## Feedback
We welcome your feedback on the package. To ask questions, request new features or report bugs, please contact Cheng Li  via chengli.email@gmail.com.

Answers to some commonly asked questions can be found in [FAQ](https://github.com/cheng-li/pyramid/wiki/FAQ).

<MSG> readme

<DFF> @@ -1,4 +1,34 @@
-Pyramid Machine Learning Library
+# Pyramid 
+
+## A Java Machine Learning Library
+
+Pyramid is a Java machine learning library which implements many state-of-the-art machine learning algorithms, including
+
+* Binary and Multi-class classification algorithms:
+    * Logistic Regression with L1 regularization (Lasso), L2 regularization (Ridge) and L1+L2 regularization (Elastic-net)
+    * Variational Bayesian Logistic Regression
+    * Gradient Boosted Trees
+    * Naive Bayes
+    * Error-Correcting Output Codes (ECOC)
+    * Support Vector Machines (SVM)
+* Multi-label classification algorithms:
+    * Binary Relevance
+    * Power Set
+    * Probabilistic Classifier Chain (PCC)
+    * Conditional Random Field (CRF)
+    * [Conditional Bernoulli Mixture (CBM)](https://github.com/cheng-li/pyramid/wiki/CBM)
+* Regression algorithms:
+    * Linear Regression with L1 regularization (Lasso), L2 regularization (Ridge) and L1+L2 regularization (Elastic-net)
+    * Variational Bayesian Linear Regression
+    * Regression Tree
+    * Gradient Boosted Trees
+* Learning to rank algorithms:
+    * LambdaMART
+* Clustering: 
+    * K Means
+    * Gaussian Mixture
+    * Bernoulli Mixture
+
 
 ## **Requirements**
 If you just want to use pyramid as a command line tool, all you need is [Java 8](http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html).
@@ -31,3 +61,6 @@ or
 Pyramid uses [Maven](https://maven.apache.org/) for its build system.
 
 To compile and package the project, simply run the `mvn clean package -DskipTests` command in the cloned directory. The compressed package will be created under the target/releases directory. Just decompress either the .zip file or the .tar.gz file and you are done.
+
+## Feedback
+We welcome your feedback on the package. To ask questions, request new features or report bugs, please email Cheng Li (chengli.email@gmail.com).
\ No newline at end of file

readme