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# HW4 | ||
There are 3 parts | ||
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First part, it's a PCA implementation | ||
Second part, its a word2vec implementation | ||
Third part, it's a dimension fuess game(?) | ||
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About the thrid problems, there's description below: | ||
>In this assignment, you have to predict the intrinsic dimension of the given sets of data points. Each set contains 10k ~ 100k data points. The data points were sampled from a Standard Normal Distribution in the intrinsic dimension (that corresponds to the particular set) and then are embedded into a higher dimension via a 3-layer neural network, with ELU activation in the first two layers and linear activation in the last layer. There are 200 sets in total. | ||
## Kagge Link | ||
<https://inclass.kaggle.com/c/ntu-ml2017-spring-hw4> | ||
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## Data Link | ||
<http:https://140.112.41.83:8000/data.npz> | ||
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### requirement.txt | ||
``` | ||
numpy | ||
scipy | ||
Pillow | ||
scikit-learn | ||
matplotlib==1.5.3 | ||
Cython | ||
word2vec | ||
nltk | ||
adjustText | ||
``` | ||
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## Reading reference: | ||
### [problem 1] | ||
<http:https://stackoverflow.com/questions/17182656/how-do-i-iterate-through-the-alphabet-in-python-please> | ||
<https://wellecks.wordpress.com/tag/eigenfaces/> | ||
<http:https://www.scipy-lectures.org/advanced/image_processing/#opening-and-writing-to-image-files> | ||
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<https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.svd.html> | ||
<https://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.load.html> | ||
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<https://docs.python.org/dev/library/argparse.html#dest> | ||
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<https://github.com/matplotlib/matplotlib/issues/1852> | ||
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### [problem 2] | ||
<http:https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html> | ||
<https://docs.python.org/2/library/os.path.html> | ||
<https://docs.python.org/3/library/functions.html#any> | ||
<https://github.com/Phlya/adjustText/blob/master/examples/Examples.ipynb> | ||
<http:https://stackoverflow.com/questions/14432557/matplotlib-scatter-plot-with-different-text-at-each-data-point> | ||
<http:https://stackoverflow.com/questions/14770735/changing-figure-size-with-subplots> | ||
<https://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.plot> | ||
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#### NLTK | ||
<http:https://www.nltk.org/data.html> | ||
<http:https://www.nltk.org/book/ch05.html> | ||
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#### word2vec | ||
<https://github.com/danielfrg/word2vec/blob/master/examples/word2vec.ipynb> | ||
<https://github.com/danielfrg/word2vec/blob/master/word2vec/scripts_interface.py> | ||
<https://www.quora.com/What-is-hierarchical-softmax> | ||
<https://arxiv.org/abs/1411.2738> | ||
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### [problem 3] | ||
<https://air.unimi.it/retrieve/handle/2434/247716/336817/phd_unimi_R09470.pdf> | ||
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<https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.permutation.html> | ||
<http:https://scikit-learn.org/stable/modules/neighbors.html> | ||
<http:https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestNeighbors.html#sklearn.neighbors.NearestNeighbors.fit> | ||
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<https://www.quora.com/Can-sklearn-algorithms-take-advantage-of-multi-core-machine> | ||
<https://www.quora.com/Does-scikit-learn-support-parallelism> | ||
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<https://docs.scipy.org/doc/numpy/reference/generated/numpy.argwhere.html#numpy.argwhere> | ||
<https://docs.scipy.org/doc/numpy/reference/generated/numpy.savez.html> | ||
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#### np.matmul = @ v.s. np.dot | ||
<http:https://stackoverflow.com/questions/6392739/what-does-the-at-symbol-do-in-python> | ||
<http:https://stackoverflow.com/questions/34142485/difference-between-numpy-dot-and-python-3-5-matrix-multiplication> | ||
<http:https://stackoverflow.com/questions/33982359/why-does-numpy-dot-behave-in-this-way/33982622> | ||
<http:https://stackoverflow.com/questions/41124979/how-using-dot-or-matmul-function-for-iterative-multiplication-in-python> | ||
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#### matplotlib $DISPLAY error on work station | ||
<http:https://stackoverflow.com/questions/2801882/generating-a-png-with-matplotlib-when-display-is-undefined> |