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nuno-aj-aniceto / tensorFlowIrisCSVrestore.py
Created June 23, 2018 18:34 — forked from mchirico/tensorFlowIrisCSVrestore.py
TensorFlow - Model has been trained, Now run it against test data.
#!/usr/bin/env python
"""
This example takes the restored values. You don't have to rebuild
the graph. But, it assumes you've trained it with the following
program:
https://gist.github.com/mchirico/bcc376fb336b73f24b29
You'll get output similar to the following
@nuno-aj-aniceto
nuno-aj-aniceto / tensorFlowIrisCSV.py
Created June 23, 2018 18:33 — forked from mchirico/tensorFlowIrisCSV.py
Tensorflow: working with tensorboard, CSV, and saving results
#!/usr/bin/env python
import tensorflow as tf
import numpy as np
from numpy import genfromtxt
# Build Example Data is CSV format, but use Iris data
from sklearn import datasets
from sklearn.model_selection import train_test_split
import sklearn
def buildDataFromIris():
@nuno-aj-aniceto
nuno-aj-aniceto / 30-income-calculon.pl
Created March 19, 2018 23:29 — forked from avar/30-income-calculon.pl
Calculate your income in The Netherlands with and without a 30% ruling.
# To check if this is up-to-date with the tax rates go to
# http://www.expatax.nl/tax-rates-2016.php and see if there's anything
# newer there.
#
# I make no guarantees that any of this is correct. I calculated this
# at the time and have been updating it when new tax rates come along
# because people keep finding this useful.
#
# There's also an interactive JS version of this created by
# @stevermeister at
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@nuno-aj-aniceto
nuno-aj-aniceto / docker-cleanup-resources.md
Created May 5, 2017 16:03 — forked from bastman/docker-cleanup-resources.md
docker cleanup guide: containers, images, volumes, networks

Docker - How to cleanup (unused) resources

Once in a while, you may need to cleanup resources (containers, volumes, images, networks) ...

delete volumes

// see: https://github.com/chadoe/docker-cleanup-volumes

$ docker volume rm $(docker volume ls -qf dangling=true)

$ docker volume ls -qf dangling=true | xargs -r docker volume rm