Category: Theano

An annotated path to start with Machine Learning

09/09/2017 Artificial Intelligence Deep Learning Generic Keras Machine Learning Neural networks Python Scikit-Learn Tensorflow Theano 2 Comments
“Do not worry about your difficulties in Mathematics. I can assure you mine are still greater.” (A. Einstein)   Machine Learning is becoming more and more widespread and, day after day, new computer scientists and engineers begin their long jump into this wonderful world. Unfortunately, the number of theories, algorithms, applications,…

Keras-based Deepdream experiment based on VGG19

07/09/2017 Convnet Deep Learning Keras Machine Learning Python Tensorflow Tensorflow Theano No Comments
Fork I’ve just published a repository (https://github.com/giuseppebonaccorso/keras_deepdream) with a Jupyter notebook containing a Deepdream (https://github.com/google/deepdream) experiment created with Keras and a pre-trained VGG19 convolutional network. The experiment (which is a work in progress) is based on some suggestions provided by the Deepdream team in this blog post but works in a slightly different…

Keras-based Neural Artistic Style Transfer

05/17/2017 Artificial Intelligence Convnet Deep Learning Keras Machine Learning Neural networks Python Tensorflow Theano No Comments
Fork I’ve just moved my Keras-based Neural Artistic Style Transfer GIST to a dedicated repository: https://github.com/giuseppebonaccorso/Neural_Artistic_Style_Transfer. Please refer always to it because the GIST is not more maintained. See also: Neural artistic style transfer experiments with Keras – Giuseppe Bonaccorso Artistic style transfer using neural networks is a technique proposed by…

BBC News classification algorithm comparison

12/05/2016 Keras Machine Learning Neural networks NLP Scikit-Learn Theano No Comments
Fork BBC News dataset (available for download in Insight Project Resources website) is made up of 2225 newslines classified into 5 categories (Politics, Sport, Entertainment, Tech, Business) and, similarly to Reuters-21578, it can be adopted in order to test both the efficacy and the efficiency of different classification strategies. In the repository: https://github.com/giuseppebonaccorso/bbc_news_classification_comparison,…