Add Prophet framework to Machine Learning

Created by: kaddynator

Prophet is a time series prediction package in python developed by Facebook. It is very useful in time series analysis and predictions providing a lot of customization options.

What is this Python project?

Describe features.

What's the difference between this Python project and similar ones?

Enumerate comparisons.

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README.md

@@ -759,11 +759,13 @@ Inspired by [awesome-php](https://github.com/ziadoz/awesome-php).
 * [H2O](https://github.com/h2oai/h2o-3) - Open Source Fast Scalable Machine Learning Platform.
 * [Metrics](https://github.com/benhamner/Metrics) - Machine learning evaluation metrics.
 * [NuPIC](https://github.com/numenta/nupic) - Numenta Platform for Intelligent Computing.
+* [Prophet ](https://facebook.github.io/prophet/docs/quick_start.html) - Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.
 * [scikit-learn](http://scikit-learn.org/) - The most popular Python library for Machine Learning.
 * [Spark ML](http://spark.apache.org/docs/latest/ml-guide.html) - [Apache Spark](http://spark.apache.org/)'s scalable Machine Learning library.
 * [vowpal_porpoise](https://github.com/josephreisinger/vowpal_porpoise) - A lightweight Python wrapper for [Vowpal Wabbit](https://github.com/JohnLangford/vowpal_wabbit/).
 * [xgboost](https://github.com/dmlc/xgboost) - A scalable, portable, and distributed gradient boosting library.
 
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 ## Microsoft Windows
 
 *Python programming on Microsoft Windows.*