Viraj G. Kulkarni (विराज गु. कुलकर्णी) virajkulkarni14

This is an incomplete, ever-changing curated list of content to assist people into the worlds of Data Science and Machine Learning. If you have a recommendation for something to add, please let me know. If something isn't here, it doesn't mean I don't recommend it, I just may not have had a chance to review it yet or not.

I will generally list things in order of easier to more formal/challenging content.

It may feel like there is an overwhelming amount of stuff for you to learn (because there is). But, there is a guided path that will get you there in time. You need to focus on Linear Algebra, Calculus, Statistics and probably Python (or R). Your best bet is to get a Safari Books Online account (https://www.safaribooksonline.com) which you may already have access to through school or work. If not, it is a reasonable way to get access to a tremendous number of books and videos.

I'm not saying you will get what you need out of everything here, but I have read/watched at least some of all of the following an

	SignatureOwner	SHA256Hash
	00000000-0000-0000-0000-000000000000	6E340B9CFFB37A989CA544E6BB780A2C78901D3FB33738768511A30617AFA01D
	77fa9abd-0359-4d32-bd60-28f4e78f784b	80B4D96931BF0D02FD91A61E19D14F1DA452E66DB2408CA8604D411F92659F0A
	77fa9abd-0359-4d32-bd60-28f4e78f784b	F52F83A3FA9CFBD6920F722824DBE4034534D25B8507246B3B957DAC6E1BCE7A
	77fa9abd-0359-4d32-bd60-28f4e78f784b	C5D9D8A186E2C82D09AFAA2A6F7F2E73870D3E64F72C4E08EF67796A840F0FBD
	77fa9abd-0359-4d32-bd60-28f4e78f784b	363384D14D1F2E0B7815626484C459AD57A318EF4396266048D058C5A19BBF76
	77fa9abd-0359-4d32-bd60-28f4e78f784b	1AEC84B84B6C65A51220A9BE7181965230210D62D6D33C48999C6B295A2B0A06
	77fa9abd-0359-4d32-bd60-28f4e78f784b	E6CA68E94146629AF03F69C2F86E6BEF62F930B37C6FBCC878B78DF98C0334E5
	77fa9abd-0359-4d32-bd60-28f4e78f784b	C3A99A460DA464A057C3586D83CEF5F4AE08B7103979ED8932742DF0ED530C66
	77fa9abd-0359-4d32-bd60-28f4e78f784b	58FB941AEF95A25943B3FB5F2510A0DF3FE44C58C95E0AB80487297568AB9771

How to add a collapsible section in markdown

1. Example

Click me

Heading

Foo
Bar
- Baz

Qux

Shallow

Real unit test (isolation, no children render)

Simple shallow

Calls:

constructor
render

	<body>
	<div id="⚛️"></div>
	<script src="https://unpkg.com/[email protected]/umd/react.development.js"></script>
	<script src="https://unpkg.com/[email protected]/umd/react-dom.development.js"></script>
	<script src="https://unpkg.com/[email protected]/babel.js"></script>
	<script type="text/babel">
	ReactDOM.render(<div>Hello World!</div>, document.getElementById('⚛️'))
	</script>
	</body>

	export ZSH=$HOME/.oh-my-zsh
	export DEFAULT_USER='athityakumar'
	TERM=xterm-256color
	ZSH_THEME="powerlevel9k/powerlevel9k"
	POWERLEVEL9K_MODE='awesome-fontconfig'

	POWERLEVEL9K_PROMPT_ON_NEWLINE=true
	POWERLEVEL9K_PROMPT_ADD_NEWLINE=true
	POWERLEVEL9K_RPROMPT_ON_NEWLINE=true
	POWERLEVEL9K_SHORTEN_DIR_LENGTH=2

	/**
	* Deal with the localStorage avoiding odd issues due to paranoids that have disabled it by default
	*/
	const ls = window.localStorage

	/**
	* Call any method on the localStorage avoiding to throw errors
	* @param {string} method - method we want to call
	* @param {array} args - serialized params that will be proxied to the method we are going to call
	* @returns {null\|string} whatever the method call will return

	import React, { Component } from 'react';

	const withDeferRender = Presentational =>
	class DeferRender extends Component {
	state = {
	shouldRender: false,
	};

	componentDidMount() {
	window.requestAnimationFrame(() => {

	// original gist
	const shuffleArray = arr => arr.sort(() => Math.random() - 0.5);

	// fully random by @BetonMAN
	const shuffleArray = arr => arr
	.map(a => [Math.random(), a])
	.sort((a, b) => a[0] - b[0])
	.map(a => a[1]);

	shuffleArray([1, 2, 3]) //[3, 1, 2]