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First of all, please do install Anaconda 5.3 in your machine
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Go to the .\Scripts folder and run the script that will perform the environment setup:
- environment.bat (if you are running Windows)
- ./environment.sh (for you, Linux folks)
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Once the script finishes running, that environment will be active. The name of the environment is aitech18-deeplearningworkshop, in case you want to activate it manually.
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If you plan on using GPU - and you should! - install the CUDA toolkit from this link to the NVIDIA web page.
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Run the main.py to check that the environment and dependencies have been properly setup. The output will show the version of the Tensorflow and Keras distributions, as well as the number of CPUs and GPUs available in our machine.
The workshop will use the following datasets:
- MNIST Hand Written Digits
The data is not provided in this repo, but instead needs to be downloaded and processed sepparately. These can be downloaded, and have the needed transformations applied automatically, by running the following Python command from the utils directory:
python retrieve_datasets.py
Both datasets are described to a greater extent in the next sections:
The initial exercises of this workshop will use the MNIST Handwritten Digits database; this publicly available dataset has become a sort of de facto industry standard to test the performance of certain image classification algorithms. Even though a detailed description of this data set is not intended here (more information here), suffice to say that each image represents a handwrittend digit, from 0 to 9, as an array of 9x9 pixels.
- Eduardo Matallanas de Ávila - @matallanas
- Jose Fernández Vizoso - @jvizoso
- Pablo Álvarez Doval - @PabloDoval