Merge pull request #367 from ahmedfgad/github-actions

Move PyGAD logo to top of docs

Author: ahmedfgad

docs/source/index.md

@@ -2,6 +2,10 @@
 
 [PyGAD](https://github.com/ahmedfgad/GeneticAlgorithmPython) is an open-source Python library for building the genetic algorithm and optimizing machine learning algorithms. It works with [Keras](https://keras.io) and [PyTorch](https://pytorch.org).
 
+![PYGAD-LOGO](https://user-images.githubusercontent.com/16560492/101267295-c74c0180-375f-11eb-9ad0-f8e37bd796ce.png)
+
+*Logo designed by [Asmaa Kabil](https://www.linkedin.com/in/asmaa-kabil-9901b7b6)*
+
 > Try [Vilvik](https://vilvik.com), a free cloud-based tool powered by PyGAD. It makes optimization easier by reducing or removing the need for coding, and it shows helpful visualizations.
 
 > Run PyGAD in the cloud with [Vilvik](https://vilvik.com): push your PyGAD problem to Vilvik, let it run in the cloud, and get the results back.
@@ -16,10 +20,6 @@ Push your PyGAD problem to [Vilvik](https://vilvik.com) and run it in the cloud.
 
 [PyGAD](https://github.com/ahmedfgad/GeneticAlgorithmPython) supports different types of crossover, mutation, and parent selection operators. It lets you optimize many types of problems with the genetic algorithm by writing your own fitness function. It works with both single-objective and multi-objective optimization problems.
 
-![PYGAD-LOGO](https://user-images.githubusercontent.com/16560492/101267295-c74c0180-375f-11eb-9ad0-f8e37bd796ce.png)
-
-*Logo designed by [Asmaa Kabil](https://www.linkedin.com/in/asmaa-kabil-9901b7b6)*
-
 Besides building the genetic algorithm, PyGAD builds and optimizes machine learning algorithms. At the moment, [PyGAD](https://pypi.org/project/pygad) supports building and training (using the genetic algorithm) artificial neural networks for classification problems.
 
 The library is under active development, and new features are added often. Please contact us if you want a feature to be supported.