Class project for Data Science and Machine Learning course of Università di Salerno Computer Science Master degree, time series clustering achieved through autoencoder's training
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Updated
Jul 31, 2019 - Jupyter Notebook
Class project for Data Science and Machine Learning course of Università di Salerno Computer Science Master degree, time series clustering achieved through autoencoder's training
applying different RNN architecture to build character prediction model and a word based prediction model these model are trained on data of specific topics from wikipedia
Introduction to GBS data analysis to MSc students from Halle University in February 2024
A character-level RNN reads words as a series of characters - outputting a prediction and “hidden state” at each step, feeding its previous hidden state into each next step. We take the final prediction to be the output, i.e. which class the word belongs to.
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