Infinite Reality Solution Realitian

Multiple SSH Keys settings for different github account

create different public key

create different ssh key according the article Mac Set-Up Git

$ ssh-keygen -t rsa -C "[email protected]"

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.

General rules

Follow standard conventions.
Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
Boy scout rule. Leave the campground cleaner than you found it.
Always find root cause. Always look for the root cause of a problem.

Design rules

Deep Learning for Face Recognition (May 2016)

Popular architectures

FaceNet (Google)
- They use a triplet loss with the goal of keeping the L2 intra-class distances low and inter-class distances high
DeepID (Hong Kong University)
- They use verification and identification signals to train the network. Afer each convolutional layer there is an identity layer connected to the supervisory signals in order to train each layer closely (on top of normal backprop)
DeepFace (Facebook)
- Convs followed by locally connected, followed by fully connected

	import android.content.SharedPreferences

	/**
	* Simple extension to remove the need to call `SharedPreferences.edit()` and `SharedPreference.Editor.apply()` for
	* every preferences change.
	*/
	fun SharedPreferences.update(updateBlock: SharedPreferences.Editor.() -> Unit) {
	val editor = edit()

	updateBlock(editor)

	#!/bin/bash

	if [ -z "$1" ]; then
	echo "waiting for the following arguments: username + max-page-number"
	exit 1
	else
	name=$1
	fi

	if [ -z "$2" ]; then

	//
	// LiveFrameCaptureViewController.swift
	// SCNKit2Video
	//
	// Created by Lacy Rhoades on 11/29/16
	// Revised 7/19/17
	// Copyright © 2017 Lacy Rhoades. All rights reserved.
	//

	import Foundation

	echo
	echo "This installation sets up a P2 instance on AWS (Ubuntu 14.04 only), installs all necessary packages"
	echo "which are required for CUDA, TensorFlow, Keras, Caffe and Torch."
	echo

	# Install dependencies
	sudo apt-get update
	sudo apt-get --assume-yes upgrade
	sudo apt-get install -y build-essential git python-pip libfreetype6-dev libxft-dev libncurses-dev libopenblas-dev gfortran python-matplotlib libblas-dev liblapack-dev libatlas-base-dev python-dev python-pydot linux-headers-generic linux-image-extra-virtual unzip python-numpy swig python-pandas python-sklearn zip
	sudo pip install -U pip