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AI: Neural Network application in Complex Networks, find a core-periphery structure from data coming from Erdős–Rényi, preferential attachment (Barabasi-Albert), Core Periphery (Borgatti-Everett) and Small World (Watts-Strogatz) networks.

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.ipynb_checkpoints
.ipynb_checkpoints
 
 
graph_generators
graph_generators
 
 
presentation
presentation
 
 
Logistic_regression-Copy1.ipynb
Logistic_regression-Copy1.ipynb
 
 
NN_Complex_Network_100accuracy_demo-Copy1.ipynb
NN_Complex_Network_100accuracy_demo-Copy1.ipynb
 
 
NN_Complex_Network_100accuracy_demo-Copy2.ipynb
NN_Complex_Network_100accuracy_demo-Copy2.ipynb
 
 
NN_Complex_Network_100accuracy_demo.ipynb
NN_Complex_Network_100accuracy_demo.ipynb
 
 
NN_Complex_Network_definitivev10.ipynb
NN_Complex_Network_definitivev10.ipynb
 
 
NN_Complex_Network_definitivev11.ipynb
NN_Complex_Network_definitivev11.ipynb
 
 
NN_Complex_Network_definitivev2.ipynb
NN_Complex_Network_definitivev2.ipynb
 
 
NN_Complex_Network_definitivev3.ipynb
NN_Complex_Network_definitivev3.ipynb
 
 
NN_Complex_Network_definitivev4-Copy1.ipynb
NN_Complex_Network_definitivev4-Copy1.ipynb
 
 
NN_Complex_Network_definitivev5.ipynb
NN_Complex_Network_definitivev5.ipynb
 
 
NN_Complex_Network_definitivev6.ipynb
NN_Complex_Network_definitivev6.ipynb
 
 
NN_Complex_Network_definitivev7.ipynb
NN_Complex_Network_definitivev7.ipynb
 
 
NN_Complex_Network_definitivev8.ipynb
NN_Complex_Network_definitivev8.ipynb
 
 
NN_Complex_Network_definitivev9.ipynb
NN_Complex_Network_definitivev9.ipynb
 
 
README.md
README.md
 
 
average_deg_core_per
average_deg_core_per
 
 
line_scrambler!.ipynb
line_scrambler!.ipynb
 
 
matrix_creator_2.ipynb
matrix_creator_2.ipynb
 
 
matrix_creator_deprecated_NON_SCRAMBLED.ipynb
matrix_creator_deprecated_NON_SCRAMBLED.ipynb
 
 
matrix_creator_scrambled!.ipynb
matrix_creator_scrambled!.ipynb
 
 
parameters.txt
parameters.txt
 
 

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This is the assignment I wrote for my Complex Networks course, attended in AA 2022/2023 at Università degli studi di Palermo, my prof. was Salvatore Miccichè.

Part of the code is taken from Coursera assignment in the Deep Learning and AI specialization course.

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AI: Neural Network application in Complex Networks, find a core-periphery structure from data coming from Erdős–Rényi, preferential attachment (Barabasi-Albert), Core Periphery (Borgatti-Everett) and Small World (Watts-Strogatz) networks.

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