Update README.md

menouarazib · Sep 18, 2023 · 77ea251 · 77ea251
1 parent 455eea1
commit 77ea251
Show file tree

Hide file tree

Showing 2 changed files with 4 additions and 4 deletions.
diff --git a/README.md b/README.md
@@ -15,7 +15,7 @@ Universal Event Detection in Time Series
 
 - [Introduction](#introduction)
 - [Installation](#installation)
-- [Quickstart](#quickstart)
+- [Quickstart](#quickstart-examples)
 - [Make Prediction](#make-prediction)
 - [Documentation](#documentation)
 - [How to credit our package](#how-to-credit-our-package)
@@ -68,7 +68,7 @@ env\Scripts\activate.bat  # for Windows
 
 <pre><code>pip install -r requirements.txt</code></pre>
 
-## Quickstart Example
+## Quickstart Examples
 ### Data sets
 To quickly get started with `EventDetector`, follow the steps below:
 

diff --git a/pyproject.toml b/pyproject.toml
@@ -17,8 +17,8 @@ build-backend = "flit_core.buildapi"
 
 [project]
 name = "eventdetector_ts"
-version = "1.0.7"
-description = "This package provides an easy-to-use and efficient solution for event detection in time series data. It includes various functionalities and tools that enable users to apply our framework to their own data sets and customize the detection process according to their specific needs."
+version = "1.0.8"
+description = "This package offers an implementation of the method outlined in the paper, Universal Event Detection in Time Series. It is designed to empower users to apply this method to their own datasets and tailor the detection process to meet their unique requirements."
 keywords = ["Event Detection", "Time Series", "Universal Approximation Theory", "Deep Learning", "Stacking Ensemble Learning"]
 authors = [
     { name = "Menouar Azib", email = "menouar.azib@akkodis.com" }