Preslav Rachev preslavrachev

Studying for a Tech Interview Sucks, so Here's a Cheat Sheet to Help

This list is meant to be a both a quick guide and reference for further research into these topics. It's basically a summary of that comp sci course you never took or forgot about, so there's no way it can cover everything in depth. It also will be available as a gist on Github for everyone to edit and add to.

Data Structure Basics

###Array ####Definition:

Stores data elements based on an sequential, most commonly 0 based, index.
Based on tuples from set theory.

Setting Up a New Mac for Development

Command-Line Utilities

Homebrew

An absolute must. If you have ever worked with apt-get on Ubuntu, you know that it's the absolute developer bliss. Homebrew (or brew for short) is the missing package manager for OSX. Not only does it allow you to install/unisnstall/manage software with a few simple commands, the same way that apt-get does. It allows you to access and install ports of most of the cross-platform utilities that you might be familiar with from Linux, over to OSX.

Installing Brew

Simply open a new terminal and execute the following command:

ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"

Hamcrest Cheatsheet

Collection Matchers

Check if a collection contains a single item

assertThat(collection, hasItem("item1"));
assertThat(collection, not(hasItem("item2")));

Kotlin Basics: Create Executable Kotlin JARs, using Gradle

Kotlin is great for creating small command-line utilities, which can be packaged and distributed as normal JAR files. This short tutorial will show you how to:

Set up a Gradle project that supports Kotlin
Add a starting function
Configure your build to call this function when you execute your JAR.

Setting up Kotlin dependencies

Daily Idea: Use CNNs to Categorize Apps, Based on Their App Store Screenshots

The idea is rather simple and feasible, but as of this moment, not really useful. It just popped up in my mind, and I decided to write it down in case someone is looking for a ML challenge to work on. The idea is very simple:

Use the iTunes Search API to download app screenshots and categorize them by folders, corresponding to the names of categories that those apps have been featured in.
Teach a simple convolutional neural network (CNN) to categorize apps based on screenshots provided
Try and evaluate the NNs capabilities using screenshots that are not present in the model.

This is a simple grayscale filter implementening image.Image. It can be used in place where an image.Image is expected.

img, err := loadImage("input.jpg")
// check error

err := saveImage(&GrayscaleFilter{img})
//check error

	/**
	* This gulpfile will copy static libraries and a index.html file as well as
	* merge, babelify and uglify the rest of the javascript project.
	*
	* TODO:
	* - Separate media, libs and src with different watchers.
	* - Media and libs should only be copied to dist if they are different sizes.
	*
	* The expected project is to be laid out as such:
	*

	private Class<?> deduceMainApplicationClass() {
	try {
	StackTraceElement[] stackTrace = new RuntimeException().getStackTrace();
	for (StackTraceElement stackTraceElement : stackTrace) {
	if ("main".equals(stackTraceElement.getMethodName())) {
	return Class.forName(stackTraceElement.getClassName());
	}
	}
	}
	catch (ClassNotFoundException ex) {

	public class DateUtil {

	public static Date asDate(LocalDate localDate) {
	return Date.from(localDate.atStartOfDay().atZone(ZoneId.systemDefault()).toInstant());
	}

	public static Date asDate(LocalDateTime localDateTime) {
	return Date.from(localDateTime.atZone(ZoneId.systemDefault()).toInstant());
	}

	// src/index.ts

	import React, { Component } from 'react';
	import {
	StyleSheet,
	Text,
	View,
	ViewStyle,
	TextStyle
	} from 'react-native';