This file contains 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
{ | |
"content_scripts": [ | |
{ | |
"matches": ["http://*/*", "https://*/*"], | |
"js": ["inject.js"], | |
"all_frames": true | |
} | |
], | |
"web_accessible_resources": [ | |
"content.js" |
This file contains 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
## based on the blogpost here: http://blog.sjas.de/posts/colored-iptables-output.html | |
iptables --line-numbers -vnL |\ | |
sed -E 's/^Chain.*$/\x1b[4m&\x1b[0m/' |\ | |
sed -E 's/^num.*/\x1b[33m&\x1b[0m/' |\ | |
sed -E '/([^y] )((REJECT|DROP))/s//\1\x1b[31m\3\x1b[0m/' |\ | |
sed -E '/([^y] )(ACCEPT)/s//\1\x1b[32m\2\x1b[0m/' |\ | |
sed -E '/([ds]pt[s]?:)([[:digit:]]+(:[[:digit:]]+)?)/s//\1\x1b[33;1m\2\x1b[0m/' |\ | |
sed -E '/([[:digit:]]{1,3}\.){3}[[:digit:]]{1,3}(\/([[:digit:]]){1,3}){0,1}/s//\x1b[36;1m&\x1b[0m/g' |\ | |
sed -E '/([^n] )(LOGDROP)/s//\1\x1b[33;1m\2\x1b[0m/'|\ |
This file contains 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
from keras.models import Sequential | |
from keras.layers.core import Dense, Dropout, Activation | |
from keras.optimizers import SGD | |
import numpy as np | |
X = np.array([[0,0],[0,1],[1,0],[1,1]]) | |
y = np.array([[0],[1],[1],[0]]) | |
model = Sequential() | |
model.add(Dense(8, input_dim=2)) |
This file contains 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 numpy as np | |
from keras.models import Sequential | |
from keras.layers import Dense | |
# dataset | |
trainX = np.array([1, 2 ,3 ,4 , 5 , 6 , 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]) | |
trainY = np.array([3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45, 48, 51, 54, 57, 60, 63, 66, 69, 72]) | |
# create a model | |
model = Sequential() |