Introduction to Deep Learning

The following material was used during the Data Mining course of the faculty of Statistics at University of Padua.

Into this repository, there are 2 case studies for a beginning approach to the deep learning:

• MNIST case study: image recognition use case, solved using a convolutional neural network
• IMDB case study: sentiment analysis use case, solved using a recurrent neural network

The analyses are implemented in R programming language, using the keras library.

For each case study, you can find:

• An R markdown notebook, in english language
• An R markdown notebook, in italian language
• An R script, with just the code

References

• Efron, Bradley, and Trevor Hastie. Computer age statistical inference. Vol. 5. Cambridge University Press, 2016.

• Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. Deep learning. MIT press, 2016.

• François, Chollet. "Deep learning with Python." (2017).

• THE MNIST DATABASE of handwritten digits.

• Large Movie Review Dataset.

• Aere, Alessandro. "Proprietà statistiche di modelli per il deep learning." (2017).