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These are the assignments (code + report) of the Artificial Neural Networks and Deep Architectures course in my master's degree in Data Science at KTH (Stockholm, Sweden).

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alvarorgaz/Artificial-Neural-Networks-and-Deep-Architectures-KTH

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Artificial Neural Networks-and-Deep-Architectures (KTH DD2437)

Author:

I am Álvaro Orgaz Expósito, a data science student at KTH (Stockholm, Sweden) and a statistician from UPC-UB (Barcelona, Spain).

Abstract:

This repository contains the assignments (code + report) of the ANN and Deep Architectures course in my master's degree in Data Science at KTH (Stockholm, Sweden).

  • Assignment 1: Learning and generalisation in feed-forward networks from perceptron learning to backpropagation.

  • Assignment 2: Radial basis functions (RBF), competitive learning and self-organised maps (SOM).

  • Assignment 3: Hopfield networks.

  • Assignment 4: Deep neural network architectures with autoencoders using Keras (applied to MNIST images dataset).

Code:

The project has been developed in Python using Jupyter Notebook.

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These are the assignments (code + report) of the Artificial Neural Networks and Deep Architectures course in my master's degree in Data Science at KTH (Stockholm, Sweden).

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