urakozz

"use strict";

let https = require("https");


let headers = {
    "Accept": "application/json;v=1.8",
    "Origin": "https://de.drive-now.com",
    "X-Language": "de",

urakozz

package main

import "fmt"
import (
	"context"
	"time"
	"math/rand"
	"sync"
)

urakozz

package main

import (
	"log"
	"net"
	"strconv"
	"time"
)

const (

urakozz

ffmpeg -reconnect 1 -reconnect_at_eof 1 -reconnect_streamed 1 -reconnect_delay_max 2000 \
-timeout 2000000000 -y -thread_queue_size 5512 -nostdin -hide_banner -fflags +genpts \
-probesize 10000000 -analyzeduration 15000000 -strict -2 \
-i "http://185.38.12.37/sec/1507602961/37303231b693a468b631da8dce8ab261f039288f1e73a0e5/ivs/69/18/89f2c8aa6418.mp4/hls/tracks-1,4/index.m3u8" 2bg.s04e07.ts

urakozz

#!/bin/bash 

export PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 

if [ "$(id -u)" != "0" ]; then 
echo "This script must be executed as root. Exiting" >&2 
exit 1 
fi 

urakozz

1. jQuery book quick overview

Intro 1

2. https://eu.udacity.com/course/intro-to-javascript--ud803 Lightweight + jQuery book as a reference
3. Start https://freecodecamp.org about 30-60 min/day

Terminal

• https://eu.udacity.com/course/shell-workshop--ud206 intro to terminal
• https://medium.freecodecamp.org/learn-the-basics-of-git-in-under-10-minutes-da548267cc91 Git quick

urakozz

package main

import "io"

func main() {

}

// Storager - interface, naming recommendation is to have 'er' ending 
type Storager interface {

urakozz

const admin = require("firebase-admin");

const serviceAccountOld = require("./../../.serviceAccountKey.json");
const serviceAccountNew = require("./../../.serviceAccountKey-new.json");
const appOld = admin.initializeApp({
    credential: admin.credential.cert(serviceAccountOld),
    databaseURL: "https://old.firebaseio.com",
}, "old");
const appNew = admin.initializeApp({
    credential: admin.credential.cert(serviceAccountNew),

urakozz

import * as tf from "@tensorflow/tfjs-node";

// In my case I have 256x256 pictures
const IMG_SIZE = 256;
const NUMBER_OF_CHANNELS = 3;

// Batch normalisation and ReLU always go together, let's add them to the separate function
const batchNormRelu = (input: tf.Tensor4D) => {
    const batch = tf.layers.batchNormalization().apply(input);
    return tf.layers.reLU().apply(batch);