Scott Sievert stsievert
stsievert
/ fftconv-conv-timings-2d.ipynb
Created
July 24, 2019 16:39
constant timing for convolution methods (fft and direct)
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stsievert
/ redirect-choice.html
Last active
April 4, 2019 23:23
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| <head> | |
| <meta http-equiv="content-type" content="text/html; charset=utf-8" /> | |
| <meta http-equiv="expires" content="0"> | |
| <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> | |
| <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> | |
| <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/css/bootstrap.min.css"> | |
| <script src="https://ajax.googleapis.com/ajax/libs/jquery/2.1.3/jquery.min.js"></script> | |
| <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/js/bootstrap.min.js"></script> | |
| </head> |
stsievert
/ test_scipy_convolve.py
Created
January 28, 2019 21:28
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| import numpy as np | |
| from scipy.signal import convolve | |
| def test(type1, type2): | |
| np.random.seed(42) | |
| n = 3000 | |
| if 'int' in type1 or 'bool' in type1: | |
| x1 = np.random.choice([0, 1], size=n).astype(type1) | |
| else: | |
| x1 = np.random.randn(n).astype(type1) |
stsievert
/ inc-search.py
Last active
November 1, 2018 04:58
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| from dask_ml.model_selection import RandomizedSearchCV | |
| from dask_ml.wrappers import Incremental | |
| from dask_ml.datasets import make_classification | |
| from sklearn.linear_model import SGDClassifier | |
| import numpy as np | |
| from sklearn.model_selection import KFold | |
| X, y = make_classification(chunks=20) | |
| params = {'estimator__alpha': np.logspace(-3, 0)} |
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stsievert
/ _Hyperband-example-test-patience.ipynb
Last active
September 10, 2018 18:52
Testing patience for hyperparam search
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stsievert
/ _Hyperband-example.ipynb
Last active
April 14, 2019 23:12
Hyperparameter comparisons (with successive halving, hyperband, stop on plateau and passive random sampling)
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stsievert
/ a-incremental-model-selection.ipynb
Created
August 22, 2018 23:31
Successive halving and "stop on plateau" comparison
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