For SVHN Dataset- http://ufldl.stanford.edu/housenumbers/ (Format 2 - train_32x32.mat, test_32x32.mat,extra_32x32.mat) In python 1. Preprocess it . executing it
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For SVHN Dataset- http://ufldl.stanford.edu/housenumbers/ (Format 2 - train_32x32.mat, test_32x32.mat,extra_32x32.mat)
In python
1. Preprocess it . executing it will generate a set of processed files.
2. Visualization - treat images as numbers. They are just matrices computer percentage of image that has dark vs light pixels, average color of each image, the number of digits that occur in image etc. Executing it will generate all of the visuals for your data, provided processed data files already exist
3. after doing visualization, for that find correlations.
use libraries only
- tensorflow
- matplotlib
- numpy
- pandas
- requests
- beautifulsoup4
- NLTK
Related Book For
Process Dynamics And Control
ISBN: 978-0471000778
2nd Edition
Authors: Dale E. Seborg, Thomas F. Edgar, Duncan A. Mellich
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