I hereby claim:
- I am 23pointsNorth on github.
- I am 23pointsnorth (https://keybase.io/23pointsnorth) on keybase.
- I have a public key whose fingerprint is 5CA6 9344 602A 2200 C452 99B0 57F6 8CE9 65C6 6EF0
To claim this, I am signing this object:
<head> | |
<style> | |
body { | |
background-color: #fefbd8; | |
} | |
h1 { | |
background-color: #80ced6; | |
} |
# This is based on code examples here | |
# https://docs.bokeh.org/en/latest/docs/user_guide/tools.html | |
# And has been modified to be abstracted better. | |
import json | |
from pathlib import Path | |
import numpy as np | |
from bokeh.embed import json_item | |
from bokeh.io import output_file, show |
from flask import Flask, render_template | |
from flask.ext.security import SQLAlchemyUserDatastore, Security | |
from flask.ext.sqlalchemy import SQLAlchemy | |
from flask.ext.bootstrap import Bootstrap | |
from flask_mail import Mail | |
from flask.ext.security import UserMixin, RoleMixin | |
app = Flask(__name__) |
import csv | |
import matplotlib.pyplot as plt | |
import matplotlib as mpl | |
import numpy as np | |
def movingaverage(interval, window_size): | |
window= np.ones(int(window_size))/float(window_size) | |
return np.convolve(interval, window, 'same') | |
'''This script demonstrates how to build a variational autoencoder | |
with Keras and deconvolution layers. | |
Reference: "Auto-Encoding Variational Bayes" https://arxiv.org/abs/1312.6114 | |
''' | |
import numpy as np | |
# import matplotlib.pyplot as plt | |
from keras.layers import Input, Dense, Lambda, Flatten, Reshape | |
from keras.layers import Convolution2D, Deconvolution2D |
#!/usr/bin/python | |
""" | |
Author: Jeremy M. Stober | |
Program: GP.PY | |
Date: Thursday, July 17 2008 | |
Description: Example of Gaussian Process Regression. | |
""" | |
from numpy import * | |
import pylab |
I hereby claim:
To claim this, I am signing this object: