Merge pull request #454 from stelios-c/patch-1

Fix typo learing -> learning in README.md

Author: ThomasMBury

README.md

@@ -12,7 +12,7 @@
 
 Many systems in nature and society can undergo critical transitions—sudden, often irreversible shifts in dynamics. Examples include the outbreak of disease, ecosystem collapse, and cardiac arrhythmias. Mathematically, such transitions often correspond to bifurcations (tipping points) in an underlying dynamical system.
 
-[Scheffer et al. (2009)](https://www.nature.com/articles/nature08227) proposed early warning signals (EWS) for bifurcations based on noisy fluctuations in time series data, sparking a surge of related ways to predict bifurcations (see [Dakos et al. (2024)](https://esd.copernicus.org/articles/15/1117/2024/esd-15-1117-2024.html) for a recent review). More recently, deep learing has shown great potential for predicting bifurcations and their type ([Bury et al. 2021](https://www.pnas.org/doi/10.1073/pnas.2106140118)).
+[Scheffer et al. (2009)](https://www.nature.com/articles/nature08227) proposed early warning signals (EWS) for bifurcations based on noisy fluctuations in time series data, sparking a surge of related ways to predict bifurcations (see [Dakos et al. (2024)](https://esd.copernicus.org/articles/15/1117/2024/esd-15-1117-2024.html) for a recent review). More recently, deep learning has shown great potential for predicting bifurcations and their type ([Bury et al. 2021](https://www.pnas.org/doi/10.1073/pnas.2106140118)).
 
 `ewstools` is a Python package for computing and visualizing EWS in time series. It complements the R package by ([Dakos et al. 2012](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0041010)) and meets growing demand for Python-based tools ([PYPL, 2022](https://pypl.github.io/PYPL.html)).