Shashank Shekhar shkr

Direct links to free Springer books (pdf versions)

duplicates = multiple editions

	import cv2
	# variables
	# distance from camera to object(face) measured
	Known_distance = 30 #centimeter
	# width of face in the real world or Object Plane
	Known_width =14.3
	# Colors
	GREEN = (0,255,0)
	RED = (0,0,255)
	WHITE = (255,255,255)

	import logging
	import os, sys
	import abc
	import gym
	import numpy as np
	import json
	from os import listdir
	from os.path import isfile, join

	gym.scoreboard.api_key = "sk_hJMbMlYzSpSsucakOMOULg"

	#!/bin/bash

	# stop on error
	set -e

	############################################

	# Dependencies

	sudo apt-get install build-essential checkinstall

	import org.apache.spark.sql.Column

	/**
	* Optimized Median calculation for a distributed dataframe built on three findings :
	* 1. Real world datasets are made from low cardinality domains
	* 2. Median calculation requires sort which is O(N * log N), it implies that computation time increase by a factor significantly greater than 2 for a list twice as long.
	* 3. Hive UDF support only primitive data types hence in the algo the datastructure transferred to a single node is a Seq[String] instead of Seq[Struct{}]
	**/
	def insertMedianOnKey(inputDF: DataFrame,
	key: Seq[Column],

	###Python###

	# Byte-compiled / optimized / DLL files
	__pycache__/
	*.py[cod]

	# C extensions
	*.so

	# Distribution / packaging