cs401r_w2016:lab5
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cs401r_w2016:lab5 [2016/01/22 21:31] admin [Deliverable:] |
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| - | The data that you will analyzing is the famous [[http://yann.lecun.com/exdb/mnist/|MNIST handwritten digits dataset]]. You can download some pre-processed MATLAB data files below: | + | The data that you will analyzing is the famous [[http://yann.lecun.com/exdb/mnist/|MNIST handwritten digits dataset]]. You can download some pre-processed MATLAB data files from the class Dropbox, or via direct links below: |
| - | [[http://hatch.cs.byu.edu/courses/stat_ml/mnist_train.mat|MNIST training data vectors and labels]] | + | [[https://www.dropbox.com/s/23vs1osykktxbqg/mnist_train.mat?dl=0|MNIST training data vectors and labels]] |
| - | [[http://hatch.cs.byu.edu/courses/stat_ml/mnist_test.mat|MNIST test data vectors and labels]] | + | [[https://www.dropbox.com/s/47dupql5jm9alc4/mnist_test.mat?dl=0|MNIST test data vectors and labels]] |
| These can be loaded using the scipy.io.loadmat function, as follows: | These can be loaded using the scipy.io.loadmat function, as follows: | ||
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| <code python> | <code python> | ||
| import matplotlib.pyplot as plt | import matplotlib.pyplot as plt | ||
| - | plt.imshow( X.reshape(28,28).T, interpolation='nearest', cmap=matplotlib.cm.gray) | + | plt.imshow( X.reshape(28,28).T, interpolation='nearest', cmap="gray") |
| </code> | </code> | ||
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