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/* | |
* Xen domain builder -- bzImage bits | |
* | |
* Parse and load bzImage kernel images. | |
* | |
* This relies on version 2.08 of the boot protocol, which contains an | |
* ELF file embedded in the bzImage. The loader extracts this ELF | |
* image and passes it off to the standard ELF loader. | |
* | |
* This code is licenced under the GPL. |
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from comodit_client.api import Client | |
# Connect to ComodIT | |
client = Client('https://my.comodit.com/api', 'demo', '******') | |
# Define a new host | |
env = client.get_organization('Demo').get_environment('Default') | |
host = env.hosts().create('my-new-host', '', 'Demo Platform', 'Demo Distribution') | |
# Deploy the host |
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### Keybase proof | |
I hereby claim: | |
* I am eschnou on github. | |
* I am eschnou (https://keybase.io/eschnou) on keybase. | |
* I have a public key whose fingerprint is 6F43 67EB 94C4 C9FC 42F4 0AF8 6F0D CAFA 0F9A D975 | |
To claim this, I am signing this object: |
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# Awesomness in form of colors, git branch, and commit (dirty) status | |
RED="\[\033[0;31m\]" | |
YELLOW="\[\033[0;33m\]" | |
GREEN="\[\033[0;32m\]" | |
BLUE="\[\033[0;34m\]" | |
LIGHT_RED="\[\033[1;31m\]" | |
LIGHT_GREEN="\[\033[1;32m\]" | |
WHITE="\[\033[1;37m\]" | |
LIGHT_GRAY="\[\033[0;37m\]" |
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# Chatbot entraîné avec DeepQA sur les sous-titres français du corpus OpenSubtitles, avec | |
# les embeddings français de FastText. | |
# | |
# https://github.com/Conchylicultor/DeepQA/pull/83 | |
Q: Quelle est la couleur du ciel ? | |
A: Elle est bonne. | |
Q: D'où viens-tu ? | |
A: Non, je suis pas prêt. |
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# Les Fabulations de La Fontaine | |
# | |
# Une petite fable, hallucinée par un RNN ayant appris à lire du Jean de La Fontaine | |
# https://github.com/eschnou/tensorflow-rnn-lafontaine | |
LE LOUP ET LE RAT | |
[Ésope] | |
Le Lion dit: A l'entendra la vie | |
De son considérer de la sorte. | |
L'Aigle lui dit le Rat se rat des plus sont de la main de son sang, |
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import pandas as pd | |
import numpy as np | |
import matplotlib.pyplot as plt | |
df=pd.read_csv("./data/bitstampUSD.csv") | |
df['Date'] = pd.to_datetime(df['Date']*int(1e9)) | |
df.Date=pd.to_datetime(df.Date, unit = 's') | |
df = df.set_index('Date').astype('float64') |