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Screencasting Framework

The following document is a written account of the Code School screencasting framework. It should be used as a reference of the accompanying screencast on the topic.

Why you should care about screencasting?

You're probably aren't going to take the time to read this document if you're not interested, but there are a lot of nice side effects caused by learning how to create quality screencasts.

1. Communicating more effectively - At Envy Labs we produce screencasts for our clients all the time. Whether it's demoing a new feature or for a presentation for an invester, they're often much more effective and pleasent than a phone call or screen sharing.

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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.

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This is the "Iris" dataset. Originally published at UCI Machine Learning Repository: Iris Data Set, this small dataset from 1936 is often used for testing out machine learning algorithms and visualizations (for example, Scatter Plot). Each row of the table represents an iris flower, including its species and dimensions of its botanical parts, sepal and petal, in centimeters.

The HTML page provides the basic code required to load the data and display it on the page (as JSON) using D3.js.

Built with blockbuilder.org

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license: mit

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First Name	Last Name	Practica bloque II Ejercicio 1: Páginas de GitHub	B2: Practica 2 Catálogo Simple en GitHubPages
Date		Apr 11, 2018	Apr 12, 2018
Points		10.0	10.0
ABRAHAM JHARED	FLORES AZCONA	9.8	10.0
AISLIN KASSANDRA	LEGORRETA CARRASCO	10.0	9.9
ALONDRA GERALDINE	ALVAREZ PEÑA	9.0	10.0
ANDREA ISABEL	LARES CASANOVA	10.0	8.0
ANDREA MADELEINE	HIGAREDA LOPEZ	9.0	9.0

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Instalación en Ubuntu

pip3 install --user pyqt5  
sudo apt-get install python3-pyqt5  
sudo apt-get install pyqt5-dev-tools
sudo apt-get install qttools5-dev-tools

---

Configurarlo en la terminal

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Toc

Keyboard shortcuts

The IPython Notebook has two different keyboard input modes. Edit mode allows you to type code/text into a cell and is indicated by a green cell border. Command mode binds the keyboard to notebook level actions and is indicated by a grey cell border.

MacOS modifier keys:

• ⌘ : Command

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C++ Coding Standards Part 0: Automated Code Analysis

Automated analysis is the main advantage to working with a modern statically typed compiled language like C++. Code analysis tools can inform us when we have implemented an operator overload with a non-canonical form, when we should have made a method const, or when the scope of a variable can be reduced.

In short, these tools catch the most commonly agreed best practice mistakes we are making and help educate us to write better code. We will be fully utilizing these tools.

Compilers

All reasonable warning levels should be enabled. Some warning levels, such as GCC's -Weffc++ warning mode can be too noisy and will not be recommended for normal compilation.

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