Fix README typos (#5)

Author: Badr-MOUFAD

README.rst

@@ -4,13 +4,13 @@ skglm
 |image0|
 
 
-``skglm`` is a library that provide better sparse generalized linear models for scikit-learn.
+``skglm`` is a library that provides better sparse generalized linear models for scikit-learn.
 Its main features are:
 
-- **speed**: problems with millions of features can be solved in seconds. Default solvers rely on efficient coordinate descent with numba just in time compilation.
+- **speed**: problems with millions of features can be solved in seconds. Default solvers rely on efficient coordinate descent with Numba just in time compilation.
 - **flexibility**: virtually any combination of datafit and penalty can be implemented in a few lines of code.
-- **sklearn API**: all estimators are drop-in replacements for scikit-learn.
-- **scope**: support for many missing models in scikit-learn - weighted Lasso, arbitrary group penalties, non convex sparse penalties, etc.
+- **scikit-learn API**: all estimators are drop-in replacements for scikit-learn.
+- **scope**: support for many missing models in scikit-learn - weighted Lasso, arbitrary group penalties, non-convex sparse penalties, etc.
 
 
 Currently, the package handles any combination of the following datafits:
@@ -63,8 +63,8 @@ Demos & Examples
 ================
 
 In the `example section <https://mathurinm.github.io/skglm/auto_examples/index.html>`__ of the documentation,
-you will find numerous examples on real life datasets,
-timing comparison with other estimators, easy and fast ways to perform cross validation, etc.
+you will find numerous examples on real-life datasets,
+timing comparison with other estimators, easy and fast ways to perform cross-validation, etc.
 
 
 Dependencies