- OS - High Sierra 10.13
- Tensorflow - 1.4
- Xcode command line tools - 8.2 (Download from here: Xcode - Support - Apple Developer & Switch to different clang version: sudo xcode-select --switch/Library/Developer/CommandLineTools & check version: clang -v)
- Cmake - 3.7
- Bazel - 0.7.0
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
<?xml version="1.0" encoding="UTF-8"?> | |
<module type="PYTHON_MODULE" version="4"> | |
<component name="NewModuleRootManager"> | |
<content url="file://$MODULE_DIR$" /> | |
<orderEntry type="jdk" jdkName="Python 3.5.2 (~/anaconda/bin/python)" jdkType="Python SDK" /> | |
<orderEntry type="sourceFolder" forTests="false" /> | |
</component> | |
<component name="TestRunnerService"> | |
<option name="PROJECT_TEST_RUNNER" value="Unittests" /> | |
</component> |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
<?xml version="1.0" encoding="UTF-8"?> | |
<module type="PYTHON_MODULE" version="4"> | |
<component name="NewModuleRootManager"> | |
<content url="file://$MODULE_DIR$" /> | |
<orderEntry type="jdk" jdkName="Python 3.5.2 (~/anaconda/bin/python)" jdkType="Python SDK" /> | |
<orderEntry type="sourceFolder" forTests="false" /> | |
</component> | |
<component name="TestRunnerService"> | |
<option name="PROJECT_TEST_RUNNER" value="Unittests" /> | |
</component> |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/bin/bash | |
python setup.py install --single-version-externally-managed --record=record.txt | |
# Download data | |
python -m nltk.downloader -d $PREFIX/nltk_data all | |
# Remove original zip files | |
rm $PREFIX/nltk_data/**/*.zip |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
""" | |
Demonstration of ways to implement this API: | |
sanitize(user_input, stop_words) | |
Related discussions: | |
- Modifying a list while looping over it: | |
- http://stackoverflow.com/questions/1207406/remove-items-from-a-list-while-iterating-in-python | |
- Remove all occurences of a value in a list: | |
- http://stackoverflow.com/questions/1157106/remove-all-occurences-of-a-value-from-a-python-list |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
""" | |
Demonstration of ways to implement this API: | |
sanitize(user_input, stop_words) | |
Related discussions: | |
- Modifying a list while looping over it: | |
- http://stackoverflow.com/questions/1207406/remove-items-from-a-list-while-iterating-in-python | |
- Remove all occurences of a value in a list: | |
- http://stackoverflow.com/questions/1157106/remove-all-occurences-of-a-value-from-a-python-list |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# List unique values in a DataFrame column | |
# h/t @makmanalp for the updated syntax! | |
df['Column Name'].unique() | |
# Convert Series datatype to numeric (will error if column has non-numeric values) | |
# h/t @makmanalp | |
pd.to_numeric(df['Column Name']) | |
# Convert Series datatype to numeric, changing non-numeric values to NaN | |
# h/t @makmanalp for the updated syntax! |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# List unique values in a DataFrame column | |
# h/t @makmanalp for the updated syntax! | |
df['Column Name'].unique() | |
# Convert Series datatype to numeric (will error if column has non-numeric values) | |
# h/t @makmanalp | |
pd.to_numeric(df['Column Name']) | |
# Convert Series datatype to numeric, changing non-numeric values to NaN | |
# h/t @makmanalp for the updated syntax! |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import pandas as pd | |
# Calculate information value | |
def calc_iv(df, feature, target, pr=0): | |
lst = [] | |
for i in range(df[feature].nunique()): | |
val = list(df[feature].unique())[i] | |
lst.append([feature, val, df[df[feature] == val].count()[feature], df[(df[feature] == val) & (df[target] == 1)].count()[feature]]) |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import pandas as pd | |
# Calculate information value | |
def calc_iv(df, feature, target, pr=0): | |
lst = [] | |
for i in range(df[feature].nunique()): | |
val = list(df[feature].unique())[i] | |
lst.append([feature, val, df[df[feature] == val].count()[feature], df[(df[feature] == val) & (df[target] == 1)].count()[feature]]) |
OlderNewer