Title: Quickstart

# Mahout MapReduce Overview

## Getting Mahout

#### Download the latest release

Download the latest release [here](http://www.apache.org/dyn/closer.cgi/mahout/).

Or checkout the latest code from [here](http://mahout.apache.org/developers/version-control.html)

#### Alternatively: Add Mahout 0.10.0 to a maven project

Mahout is also available via a [maven repository](http://mvnrepository.com/artifact/org.apache.mahout) under the group id *org.apache.mahout*.
If you would like to import the latest release of mahout into a java project, add the following dependency in your *pom.xml*:

    <dependency>
        <groupId>org.apache.mahout</groupId>
        <artifactId>mahout-mr</artifactId>
        <version>0.10.0</version>
    </dependency>


## Features

For a full list of Mahout's features see our [Features by Engine](http://mahout.apache.org/users/basics/algorithms.html) page.

    
## Using Mahout

Mahout has prepared a bunch of examples and tutorials for users to quickly learn how to use its machine learning algorithms.

#### Recommendations

Check the [Recommender Quickstart](/users/recommender/quickstart.html) or the tutorial on [creating a userbased recommender in 5 minutes](/users/recommender/userbased-5-minutes.html).

If you are building a recommender system for the first time, please also refer to a list of [Dos and Don'ts](/users/recommender/recommender-first-timer-faq.html) that might be helpful.

#### Clustering

Check the [Synthetic data](/users/clustering/clustering-of-synthetic-control-data.html) example.

#### Classification

If you are interested in how to train a **Naive Bayes** model, look at the [20 newsgroups](/users/classification/twenty-newsgroups.html) example.

If you plan to build a **Hidden Markov Model** for speech recognition, the example [here](/users/classification/hidden-markov-models.html) might be instructive. 

Or you could build a **Random Forest** model by following this [quick start page](/users/classification/partial-implementation.html).

#### Working with Text 

If you need to convert raw text into word vectors as input to clustering or classification algorithms, please refer to this page on [how to create vectors from text](/users/basics/creating-vectors-from-text.html).