Patrick Tran theptrk

## optional_chaining.js
// This is an example of Optional Chaining
const adventurer = {
  name: 'Alice',
  cat: {
    name: 'Dinah'
  }
};

const dogName = adventurer.dog?.name;
console.log(dogName);

## app.js
// js goes here
console.log("hello js")

## html_onsubmit.html
<!DOCTYPE html>
<html>
<head>
    <title>Hello onsubmit</title>
</head>
<body>
    <h1>Hello onsubmit</h1>
    <form onsubmit="handleForm()">
        <input type="text" name="todo" autocomplete="off">
        <button type="submit">Create Todo</button>

## read_sys_path_files.sh
import sys
print(sys.path)

## recoverData.m
function X_rec = recoverData(Z, U, K)

% initialize recovered values
X_rec = zeros(size(Z, 1), size(U, 1));

for i = 1:size(X_rec,1)
    % projected_x is (1, K)
    projected_x = Z(i, :);

    % initialize x

## projectData.m
function Z = projectData(X, U, K)

% Initalize
Z = zeros(size(X, 1), K);

% index to create Ureduce
Ureduce = U(:, 1:K)

for i=1:size(Z,1)


## kMeansInitCentroids.m
function centroids = kMeansInitCentroids(X, K)

% initialize placeholder
centroids = zeros(K, size(X, 2));

% use randperm to shuffle the row indices of X
shuffle_X = randperm(size(X,1));

% only use the first K number of shuffled indices
first_K = shuffle_X(1:K, :);

## computeCentriods.m
function centroids = computeCentroids(X, idx, K)

% Initialize to store new centroid values
centroids = zeros(K, n);

% iterate over number of centroids
for i = 1:K

    % create a boolean vector that match the current index, then use this to index into X
    has_this_centroid = X(idx == i, :);

## findClosestCentriods.m
function idx = findClosestCentroids(X, centroids)

% Set K
K = size(centroids, 1);

% Set empty indices vector
idx = zeros(size(X,1), 1);

% for every example in X...
for i = 1:size(X, 1)

## binary-tree-depth-first-search.js
/**
 * Depth first search and Breadth first search traverals in JavaScript
 * This example uses a binary tree with left and right nodes
 * by theptrk <github.com/theptrk>
 */
function Node(value, opts = {}) {
  this.value = value
  this.left = opts.left ? opts.left : null
  this.right = opts.right ? opts.right : null
}
	// This is an example of Optional Chaining
	const adventurer = {
	name: 'Alice',
	cat: {
	name: 'Dinah'
	}
	};

	const dogName = adventurer.dog?.name;
	console.log(dogName);
	<!DOCTYPE html>
	<html>
	<head>
	<title>Hello onsubmit</title>
	</head>
	<body>
	<h1>Hello onsubmit</h1>
	<form onsubmit="handleForm()">
	<input type="text" name="todo" autocomplete="off">
	<button type="submit">Create Todo</button>
	function X_rec = recoverData(Z, U, K)

	% initialize recovered values
	X_rec = zeros(size(Z, 1), size(U, 1));

	for i = 1:size(X_rec,1)
	% projected_x is (1, K)
	projected_x = Z(i, :);

	% initialize x
	function Z = projectData(X, U, K)

	% Initalize
	Z = zeros(size(X, 1), K);

	% index to create Ureduce
	Ureduce = U(:, 1:K)

	for i=1:size(Z,1)
	function centroids = kMeansInitCentroids(X, K)

	% initialize placeholder
	centroids = zeros(K, size(X, 2));

	% use randperm to shuffle the row indices of X
	shuffle_X = randperm(size(X,1));

	% only use the first K number of shuffled indices
	first_K = shuffle_X(1:K, :);
	function centroids = computeCentroids(X, idx, K)

	% Initialize to store new centroid values
	centroids = zeros(K, n);

	% iterate over number of centroids
	for i = 1:K

	% create a boolean vector that match the current index, then use this to index into X
	has_this_centroid = X(idx == i, :);
	function idx = findClosestCentroids(X, centroids)

	% Set K
	K = size(centroids, 1);

	% Set empty indices vector
	idx = zeros(size(X,1), 1);

	% for every example in X...
	for i = 1:size(X, 1)
	/**
	* Depth first search and Breadth first search traverals in JavaScript
	* This example uses a binary tree with left and right nodes
	* by theptrk <github.com/theptrk>
	*/
	function Node(value, opts = {}) {
	this.value = value
	this.left = opts.left ? opts.left : null
	this.right = opts.right ? opts.right : null
	}