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from keras.models import Sequential
from keras.layers import Dense
import numpy
# fix random seed for reproducibility
numpy.random.seed(7)
# load pima indians dataset
dataset = numpy.loadtxt("pima-indians-diabetes.data.csv", delimiter=",")
@ox1111
ox1111 / ex4
Created February 15, 2019 08:28
# Create first network with Keras
from keras.models import Sequential
from keras.layers import Dense
import numpy
# fix random seed for reproducibility
seed = 7
numpy.random.seed(seed)
@ox1111
ox1111 / data
Created February 15, 2019 08:29
wget https://raw.githubusercontent.com/jbrownlee/Datasets/master/pima-indians-diabetes.data.csv
wget https://raw.githubusercontent.com/jbrownlee/Datasets/master/pima-indians-diabetes.names
6 148 72 35 0 33.6 0.627 50 1
1 85 66 29 0 26.6 0.351 31 0
8 183 64 0 0 23.3 0.672 32 1
1 89 66 23 94 28.1 0.167 21 0
0 137 40 35 168 43.1 2.288 33 1
5 116 74 0 0 25.6 0.201 30 0
3 78 50 32 88 31.0 0.248 26 1
10 115 0 0 0 35.3 0.134 29 0
2 197 70 45 543 30.5 0.158 53 1
8 125 96 0 0 0.0 0.232 54 1
sudo pip install -r requirements.txt
sudo pip install pyotp
# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
main = putStrLn "Hello World"
https://www.haskell.org/platform/
ghc --make helloworld.hs