Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/792#discussion_r32196879
--- Diff: docs/libs/ml/quickstart.md ---
@@ -24,4 +25,214 @@ under the License.
* This will be replaced by the TOC
{:toc}
-Coming soon.
+## Introduction
+
+FlinkML is designed to make learning from your data a straight-forward
process, abstracting away
+the complexities that usually come with having to deal with big data
learning tasks. In this
+quick-start guide we will show just how easy it is to solve a simple
supervised learning problem
+using FlinkML. But first some basics, feel free to skip the next few lines
if you're already
+familiar with Machine Learning (ML).
+
+As defined by Murphy [1] ML deals with detecting patterns in data, and
using those
+learned patterns to make predictions about the future. We can categorize
most ML algorithms into
+two major categories: Supervised and Unsupervised Learning.
+
+* **Supervised Learning** deals with learning a function (mapping) from a
set of inputs
+(features) to a set of outputs. The learning is done using a *training
set* of (input,
+output) pairs that we use to approximate the mapping function. Supervised
learning problems are
+further divided into classification and regression problems. In
classification problems we try to
+predict the *class* that an example belongs to, for example whether a user
is going to click on
+an ad or not. Regression problems one the other hand, are about predicting
(real) numerical
+values, often called the dependent variable, for example what the
temperature will be tomorrow.
+
+* **Unsupervised Learning** deals with discovering patterns and
regularities in the data. An example
+of this would be *clustering*, where we try to discover groupings of the
data from the
+descriptive features. Unsupervised learning can also be used for feature
selection, for example
+through [principal components
analysis](https://en.wikipedia.org/wiki/Principal_component_analysis).
+
+## Linking with FlinkML
+
+In order to use FlinkML in you project, first you have to
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