IMPORTANT!!! Some BDAP services are not available or not working correctly. This issue seems to be linked to the NetApp storage most of our services rely on. We will have to restart several servers in the coming hours and days to solve it. Thank you for your patience.
BDAP services will not be available on Friday 9 December morning and partially available in the afternoon (check email announcement for more details).
The server powering jeodpp-terminal-001-XXX and jeodpp-text-terminal-001-XXX had to be restarted on Tuesday 06 December 16:45 following an issue in the connection with the NetApp storage. Please check your files/data in case you were using one of those terminals during that time period.
|# Contents||# Contents|
|This folder contains the notebooks used in the training course "Deep Learning on the JRC Data Platform". It contains two examples. The first||This folder contains the notebooks used in the training course "Deep Learning on the JRC Data Platform". It contains four examples:|
|one uses Keras to create from scratch a Convolutional Neural Network to classify satellite images; the second one uses PyTorch to fine-tune|
|a pre-trained network for fake news detection.||- 1_keras_eurosat uses Keras to create from scratch a Convolutional Neural Network to classify satellite images|
|\ No newline at end of file||- 2_torch_on_text uses PyTorch to fine-tune a pre-trained network for fake news detection|
|- 3_torch19_on_text runs the same example but creates a Conda environment with PyTorch 1.9 installed|
|- 4_sklearn_test performs the same task using Scikit-Learn, a library with classical Machine Learning algorithms|