Learn Chrome, Natural and Ruby

Optional chaining ?. in javascript is a new feature introduced in ES2020. Optional chaining changes the way properties are accessed from deeply nested objects. It fixes the problem of having to do multiple null checks when accessing long chain of object properties in javascript.

JavaScript® (often shortened to JS) is a lightweight, interpreted, object-oriented language with first-class functions, most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic, and supports object-oriented, imperative, and functional programming styles.

javascript

Optional Chaining

Chrome DevTools are incredibly useful for a frontend developer, sometimes we spend more time using them than our text editor of choice.

That's why it's so important to understand this tool better - those quick lessons will teach you things that will help you to become a more effective developer.

You will learn how to:

- **Use (experimental) CSS Overview to learn all about CSS used on a page in a minute**
- **Style console.log messages with CSS** - a _crucial_ skill for any senior developer (j/k)
- **Debug your code (on production and local environment) with logpoints**
- **Run a Lighthouse audit of your site**
- **Choose accessible colors for your website that have an AAA contrast ratio rating**
- **Force a DOM element state in Chrome DevTools**
- **Use Console utilities to make debugging easier**
- **Copy a network request as fetch or cURL with Chrome DevTools**

Have fun!

The Chrome Developer Tools (DevTools for short), are a set of web authoring and debugging tools built into Google Chrome.

chrome-devtools

Chrome DevTools tips & tricks

In this course we’ll work through Natural’s API for natural language processing in JavaScript. We’ll look at how to process text: learning how to break up language strings, find the word roots, work with inflectors, find sequences of words, and tag parts of speech. We’ll learn how to find important stats about a body of text: how to compare strings, how to classify text with machine learning, how to use the tf-idf tool to find relevant words. We’ll look at some of the extra tools Natural gives us, including the dictionary/thesaurus of WordNet, a phonetics comparer that lets us see if two words sound the same, and a spellcheck feature. We’ll also look at tries and digraphs, two data structures that help us better analyze bodies of text.

Natural is a general natural language facility for nodejs. Tokenizing, stemming, classification, phonetics, tf-idf, WordNet, string similarity, and some inflections are currently supported.

natural

Natural Language Processing in JavaScript with Natural

In this course we’ll take a deep look at the Elements panel in the chrome devtools. We’ll step through each button and tab on this panel and discuss how to use them to interact with your web application as it runs.

Debug the DOM in Chrome with the Devtools Elements Panel

This course examines the Sources panel in the Chrome DevTools, which allows you to see what files are responsible for the various things on the screen. Bundled into this panel, though, is the single most useful tool for any JavaScript developer - the JavaScript Debugger. We’ll use the Debugger to inspect JavaScript as it runs, allowing you to watch (and even interact with) the state of your application as it runs in ways that’ll blow your mind if you’ve mostly used console.log to debug your applications to this point. 

Debug JavaScript in Chrome with DevTool Sources

This course will examine the Network panel in Chrome DevTools. We’ll step through the request log, examining the various properties exposed. We’ll talk about timing, filtering, throttling and generally using the network panel to better understand the ways in which our applications exist within a connected context.

Debug HTTP with Chrome DevTools Network Panel

Rails is a web-application framework that includes everything needed to create database-backed web applications according to the Model-View-Controller (MVC) pattern.

rails

Expanding on [Part 1](https://egghead.io/lessons/angularjs-rails-todo-api-part-1), this lesson will look at how to bootstrap AngularJS in a rails application as part of the asset pipeline. With Angular available, you'll see how to communicate with the Rails API using $resource.

Rails Todo API Part 2

We will learn about “stemming,” the process of finding the root of words, often in order to group words by a common base root. We will look at the Porter and Lancaster Stemmers, briefly touch on Natural’s support for Russian and Spanish stemmers, and introduce the function to stem and tokenize at the same time.

Find the roots of words using stemming in Natural

Inflectors are the modifiers of a word that indicate grammatical categories. While Natural’s coverage of inflectors is not comprehensive, we will show how Natural can pluralize/singularize nouns and count numbers. 

Pluralizing nouns and counting numbers with inflectors in Natural

N-grams are sequences of words, where the 'n' stands for the number of words in the sequence. In this lesson, we will see how to find bigrams (2-grams), trigrams (3-grams), and any other length n-gram in a body of text. 

Find sequences of words (n-grams) using Natural

We will learn how to compare how similar two strings are to each other, examining three algorithms: Jaro-Winkler, Levenshtein, and Dice’s Coefficient.  

You should note that none of these algorithms are inherently better than the others. Instead, it's important to choose the one that best fits your text data. 

Compare similarity of strings through string distance in Natural

In this lesson, we will learn how to train a Naive Bayes classifier or a Logistic Regression classifier - basic machine learning algorithms - in order to classify text into categories.

Classify text into categories with machine learning in Natural

In this lesson, we will learn how to train a Naive Bayes classifier and a Logistic Regression classifier - basic machine learning algorithms - on JSON text data, and classify it into categories.

While this dataset is still considered a small dataset -- only a couple hundred points of data -- we'll start to get better results.

The general rule is that Logistic Regression will work better than Naive Bayes, but only if there is enough data. Since this is still a pretty small dataset, Naive Bayes works better here. Generally, Logistic Regression takes longer to train as well. 

This uses data from Ana Cachopo: http://ana.cachopo.org/datasets-for-single-label-text-categorization

Classify JSON text data with machine learning in Natural

 AJAX allows us to send requests to the server from our javascript applications, rather than allowing the browser to directly request declaratively specified resources. Under the hood, though, AJAX requests are still just HTTP requests - and that means we can use the Network Panel in Chrome’s DevTools to inspect our AJAX operations!


Examine AJAX Requests with Chrome Devtools

Tries are a data structure that provide an efficient way to search for the existence of a word or phrase in a body of text, or to search by prefix. 

Search more efficiently with tries using Natural

To understand the Network DevTool, you have to understand what HTTP is and how it works. Let’s use the Network DevTool to inspect an HTTP request and its corresponding response so that we can understand what the browser is doing.

Analyze HTTP Requests and Responses with Chrome Devtools

Most of today’s websites use optimized, compiled, minified and obfuscated javascript and CSS. Examining this stuff here has some severely limited utility, which is why when developing we rely on sourcemaps. We’ll set up a webpack workflow that uses sourcemaps to show you how they can help your debugging!

Unbundle your JavaScript with Source Maps in Chrome DevTools

In this lesson, we’ll see how to use Natural’s probabilistic spell-checker, which uses the trie data structure. 

Include spell-check in text projects using Natural

Tf-idf, or term frequency-inverse document frequency, is a statistic that indicates how important a word is to the entire document. This lesson will explain term frequency and inverse document frequency, and show how we can use tf-idf to identify the most relevant words in a body of text. 

Identify the most important words in a document using tf-idf in Natural

Learn to use the Style panel within the Element Inspector to examine and tweak the CSS rules applied to your application as it runs. 

Chrome Devtools: Elements - Debug with Style!

The Element Inspector in Chrome DevTools offers powerful integration with the console - learn how to programmatically navigate your selected element, how to search through the history and use CSS selectors to control what you're looking at and how to quickly and easily listen for events as you debug your application.

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