Difference between revisions of "DeepLearning"
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(Created page with "===Deep Learning=== ==Numpy/Python tricks== A trick when you want to flatten a matrix X of shape (a,b,c,d) to a matrix X_flatten of shape (b ∗∗ c ∗∗ d, a) is to use: <...") |
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==Numpy/Python tricks== | ==Numpy/Python tricks== | ||
A trick when you want to flatten a matrix X of shape (a,b,c,d) to a matrix X_flatten of shape (b ∗∗ c ∗∗ d, a) is to use: | A trick when you want to flatten a matrix X of shape (a,b,c,d) to a matrix X_flatten of shape (b ∗∗ c ∗∗ d, a) is to use: | ||
| − | <pre> | + | <pre class="brush:python"> |
X_flatten = X.reshape(X.shape[0], -1).T # X.T is the transpose of X | X_flatten = X.reshape(X.shape[0], -1).T # X.T is the transpose of X | ||
</pre> | </pre> | ||
Revision as of 02:32, 8 January 2018
Deep Learning
Numpy/Python tricks
A trick when you want to flatten a matrix X of shape (a,b,c,d) to a matrix X_flatten of shape (b ∗∗ c ∗∗ d, a) is to use:
X_flatten = X.reshape(X.shape[0], -1).T # X.T is the transpose of X
