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img.img-explore { | |
opacity: 0.75; | |
} |
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import numpy as np | |
import tensorflow as tf | |
__author__ = "Sangwoong Yoon" | |
def np_to_tfrecords(X, Y, file_path_prefix, verbose=True): | |
""" | |
Converts a Numpy array (or two Numpy arrays) into a tfrecord file. | |
For supervised learning, feed training inputs to X and training labels to Y. | |
For unsupervised learning, only feed training inputs to X, and feed None to Y. |
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"""Script to illustrate usage of tf.estimator.Estimator in TF v1.3""" | |
import tensorflow as tf | |
from tensorflow.examples.tutorials.mnist import input_data as mnist_data | |
from tensorflow.contrib import slim | |
from tensorflow.contrib.learn import ModeKeys | |
from tensorflow.contrib.learn import learn_runner | |
# Show debugging output |
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"""akmtdfgen: A Keras multithreaded dataframe generator. | |
Works with Python 2.7 and Keras 2.x. | |
For Python 3.x, need to fiddle with the threadsafe generator code. | |
Test the generator_from_df() functions by running this file: | |
python akmtdfgen.py |
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"""Information Retrieval metrics | |
Useful Resources: | |
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt | |
http://www.nii.ac.jp/TechReports/05-014E.pdf | |
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf | |
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf | |
Learning to Rank for Information Retrieval (Tie-Yan Liu) | |
""" | |
import numpy as np |
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<html> | |
Hello World | |
</html> |
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<script src="https://unpkg.com/jupyter-js-widgets@~2.1.4/dist/embed.js"></script> | |
<script type="application/vnd.jupyter.widget-state+json"> | |
{ | |
"version_major": 1, | |
"version_minor": 0, | |
"state": { | |
"7da35340b651476ba3926aa15366e2d8": { | |
"model_name": "LayoutModel", | |
"model_module": "jupyter-js-widgets", | |
"model_module_version": "~2.1.4", |
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