mgei

library(tidyverse)
library(lubridate)

days <- tibble(date = seq(date("2018-01-01"), by = "days", length.out = 730)) %>% 
  mutate(day = weekdays(date))

hours <- tibble(daytype =   c("weekday", "weekday", "weekday", "weekday", "weekday", "weekend"),
                time_from = c("00:00",   "08:00",   "12:00",   "13:00",   "17:00",   "00:00" ),
                time_to =   c("08:00",   "12:00",   "13:00",   "17:00",   "23:59",   "23:59" ),
                state =     c("closed",  "open",    "closed",  "open",    "closed",  "closed"))

mgei

library(tidyverse)

localurl <- function(document, path = ""){
  
  path     <- str_remove_all(path, "/$|^/")
  document <- str_remove_all(document, "/$|^/")
  
  path     <- file.path(path, document) %>% 
    str_remove_all("/$|^/")
  document <- last(str_split(path, pattern = "/", simplify = T))

mgei

# to install the latest version 0.53 of Hugo on Ubuntu:
# releases are here: https://github.com/gohugoio/hugo/releases
export VER="0.55.5"
wget https://github.com/gohugoio/hugo/releases/download/v0.55.5/hugo_${VER}_Linux-64bit.deb
sudo dpkg -i hugo_${VER}_Linux-64bit.deb

# check if right version is installed
hugo version

# make a new website (don't do that if you already have one)

mgei

Running the sample MOVIDIUS models on Ubuntu 16.04

1. Install OpenVino Toolkit: https://software.intel.com/en-us/articles/OpenVINO-Install-Linux
2. Additional installation steps: https://software.intel.com/en-us/articles/OpenVINO-Install-Linux

Compile all models first. There's a bash for this. After that, the models are in the home directory:

cd ~/inference_engine_samples_build/intel64/Release

Weights are in a subfolder of the installation directory:

mgei

What I've done thus far

Install QMKL

But before:

Install Py-videocore

Increase video memory!

mgei

library(shiny)
library(tidyverse)

# data <- readRDS("persistent_data/data.RDS")
data <- as_tibble(mtcars) %>% head()

ui <- fluidPage(
  tableOutput("mytable"),
  actionButton("go", "filter it"),
  actionButton("save", "save it")

mgei

library(tidyverse)

library(ggplot2)

periods <- 10
trend <- 0
vola <- 0.1

leverage <- 2

mgei

library(shiny)
library(shinyWidgets)
library(tidyverse)

# read persistent data or create a new file if it does not exist yet
if ("favs.csv" %in% list.files()) {
  favs <- read_file("favs.csv") %>% 
    strsplit(", ") %>% 
    .[[1]] %>% 
    as.numeric() %>% 

mgei

library(shiny)

ui <- fluidPage(
  fluidRow(
    column(width = 12,
           tabsetPanel(
             tabItem("main", "MENU"),
             tabItem("more", uiOutput("hello"))
           ))
  )

mgei

library(tidyverse)
library(tidyquant)
library(lubridate)

# get data from Yahoo ----
spx <- tq_get("^GSPC")

# calculate returns ----
ret_daily <- spx %>% 
  mutate(ret = adjusted/lag(adjusted)-1,