From 7d876876e060ae3e034ae1bc69cce6b65dcc511d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Petr=C3=B4nio=20C=C3=A2ndido=20de=20Lima=20e=20Silva?= Date: Thu, 12 Apr 2018 18:24:32 -0300 Subject: [PATCH] Update README.md --- README.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/README.md b/README.md index 58dd252..71555fd 100644 --- a/README.md +++ b/README.md @@ -53,6 +53,12 @@ Fuzzy Time Series (FTS) are non parametric methods for time series forecasting b 7. **Data postprocessing**: The inverse operations of step 1. +## Usage examples + +There is nothing better than good code examples to start. [Then check out the demo Jupyter Notebooks of the implemented method os pyFTS!](https://github.com/petroniocandido/pyFTS/tree/master/pyFTS/notebooks). + +A Google Colab example can also be found [here](https://drive.google.com/file/d/1zRBCHXOawwgmzjEoKBgmvBqkIrKxuaz9/view?usp=sharing). + ## MINDS - Machine Intelligence And Data Science Lab This tool is result of collective effort of [MINDS Lab](http://www.minds.eng.ufmg.br/), headed by Prof. Frederico Gadelha Guimarães. Some of research on FTS which was developed under pyFTS: