mcohen01

riders = {
    'maverick': '''2:01.521 2:00.543 2:08.984 7:53.953 2:00.500 2:00.419 2:00.353 2:08.864 5:51.848 2:00.120 2:06.770 2:08.161 9:52.259 2:03.576 2:00.641 2:06.417 2:00.254 2:00.252 2:00.217 2:00.166 2:00.038 2:13.137 17:08.751 2:01.849 2:00.964 2:06.733 9:42.350 2:01.038 2:00.784 2:01.367 2:07.549 24:39.555 1:59.863 1:59.597 2:05.496 2:00.062 1:59.883 1:59.960 1:59.817 1:59.828 1:59.677 2:15.620 3:44:30.822 2:01.945 2:01.636 2:06.572 9:19.397 2:01.612 2:01.347 2:06.824 22:17.000 2:06.718 10:45.492 2:01.019 2:00.874 2:13.634 10:16.528 2:00.417 2:03.570 5:31.109 1:58.897 2:19.867''',

    'rins': '''2:02.779 2:00.252 2:00.333 2:00.085 2:16.415 11:01.027 2:00.839 2:00.884 2:00.368 2:15.964 15:53.040 2:02.111 1:59.978 2:00.418 2:20.209 25:23.315 2:00.811 2:00.327 2:00.160 2:21.776 15:53.420 2:01.575 2:00.384 2:00.848 2:20.687 30:34.733 2:01.857 2:00.412 2:00.544 2:18.916 12:19.015 2:01.598 2:01.679 2:10.196 3:08:39.528 2:03.096 2:00.363 2:00.273 2:00.346 2:10.362 11:24.587 2:00.415 2:00.212 2:00.481 2:

mcohen01

mcohen01

library(forecast)

hourly_boots <- read.csv('hourly_boots.csv', header = F)
names(hourly_boots) <- c('time', 'value')

ts.index <- seq(from = as.POSIXct("2018-12-17 00:00"),
                to = as.POSIXct("2019-03-09 23:00"),
                by="hour")

periods <- msts(hourly_boots$value, seasonal.periods = c(24, 24*7))

mcohen01

mcohen01

main {
  max-width: 38rem;
  padding: 2rem;
  margin: auto;
}

/* 
https://jrl.ninja/etc/1/
https://jgthms.com/web-design-in-4-minutes/#centering 
https://news.ycombinator.com/item?id=19607169

mcohen01

{'activities-heart': [{'dateTime': '2019-05-01', 'value': {'customHeartRateZones': [], 'heartRateZones': [{'caloriesOut': 101.92, 'max': 87, 'min': 30, 'minutes': 29, 'name': 'Out of Range'}, {'caloriesOut': 157.248, 'max': 122, 'min': 87, 'minutes': 29, 'name': 'Fat Burn'}, {'caloriesOut': 146.72, 'max': 148, 'min': 122, 'minutes': 13, 'name': 'Cardio'}, {'caloriesOut': 252.56, 'max': 220, 'min': 148, 'minutes': 19, 'name': 'Peak'}]}}], 'activities-heart-intraday': {'dataset': [{'time': '00:00:13', 'value': 65}, {'time': '00:00:28', 'value': 65}, {'time': '00:00:43', 'value': 65}, {'time': '00:00:58', 'value': 65}, {'time': '00:01:13', 'value': 65}, {'time': '00:01:28', 'value': 65}, {'time': '00:01:32', 'value': 65}, {'time': '00:01:47', 'value': 65}, {'time': '00:02:02', 'value': 65}, {'time': '00:02:17', 'value': 65}, {'time': '00:02:32', 'value': 65}, {'time': '00:02:47', 'value': 65}, {'time': '00:03:02', 'value': 65}, {'time': '00:03:17', 'value': 65}, {'time': '00:03:32', 'value': 65}, {'time': '00:03

mcohen01

import json
import numpy as np
import pandas as pd
import glob
from PIL import Image
from sklearn.model_selection import train_test_split

from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D
from keras.layers import Activation, Dropout, Flatten, Dense

mcohen01

gcloud config set compute/zone us-central1-c

gcloud compute instances create tpu-demo-vm --machine-type=n1-standard-4 --boot-disk-size=500GB --image-project=ml-images --image-family=tf-1-8 --scopes=cloud-platform

gcloud beta compute tpus create demo-tpu --range=10.240.1.0/29 --version=1.13 --network=default

gcloud compute ssh tpu-demo-vm

export TPU_NAME="demo-tpu"

mcohen01

tar czf Downloads.tar.gz Downloads
tar czf Sites.tar.gz Sites
tar czf dots.tar.gz .aliases .aws .bash .bash_history .bash_profile .bash_prompt .bashrc .boto .config .curlrc .docker .dropbox .exports .gitconfig .gnupg .gsutil .hushlogin .inputrc .ipython .iterm2 .iterm2_shell_integration.bash .lein .mysql_history .profile .psql_history .sh_history .ssh .vim .viminfo .vimrc .vscode
tar czf Postgresql.tar.gz /usr/local/var/postgres/

gsutil cp Downloads.tar.gz gs://mcohen01-backup
gsutil cp Sites.tar.gz gs://mcohen01-backup
gsutil cp dots.tar.gz gs://mcohen01-backup
gsutil cp Postgresql.tar.gz gs://mcohen01-backup

mcohen01