Included some more info in README

README.md

@@ -4,9 +4,25 @@
 [![codecov](https://codecov.io/gh/facusapienza21/SphereUDE.jl/graph/badge.svg?token=UC0KFSUU3X)](https://codecov.io/gh/facusapienza21/SphereUDE.jl)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 
+SphereUDE.jl is a Julia package for non-parametric regression of data supported in the three-dimensional sphere. 
+It implements a simple universal differential equation (UDE) that naturaly constrains path to lie in the sphere. 
+This has important application in Paleomagnetism, where the objective is to fit Aparent Polar Wander Paths (APWPs) to recunstruct continents past motion. 
+In addition to sphere regression, SphereUDE.jl implements a series of improvements over previous modelling methods, such as 
+- Explicit sphere constrint that allows for univesality of regression 
+- Regularization on the path to incorporate physical priors 
+- Incorporation of temporal and spatial uncertanties
+- Uncertanty quantification capabilities
 
+## Installing SphereUDE
 
-## Python setup
+In order to install `SphereUDE` in a given environment, just do in the REPL:
+```julia
+julia> ] # enter Pkg mode
+(@v1.9) pkg> activate MyEnvironment # or activate whatever path for the Julia environment
+(MyEnvironment) pkg> add SphereUDE
+```
+
+## SphereUDE initialization: integration with Python
 
 In order to make plots using Matplotlib, Cartopy, and PMagPy, we install both [PyCall.jl](https://github.com/JuliaPy/PyCall.jl) and [PyPlot.jl](https://github.com/JuliaPy/PyPlot.jl) and execute Python code directly from Julia. In order to do this setup manually, you can follow the next steps.