Learn Grep, Natural and Ngrx-store

As your Angular application grows, it becomes more difficult to manage application state.

NgRx can help with that!

In this course, we will learn how to convert an Angular application from using stateful services into using NgRx.

We will accomplish this by adding a new feature, including building a reducer and actions. We'll also touch on using selectors to query our state, managing collections with NgRx entity, async operations, and hiding implementation details with the facade pattern.

Angular is a development platform for creating applications using modern web standards. Angular includes a wealth of essential features such as mobile gestures, animations, filtering, routing, data binding, security, internationalization, and beautiful UI components. It's extremely modular, lightweight, and easy to learn.

angular

Reactive State Management in Angular with ngrx

CMD+F in your text editor can only get you so far! In this course, we will learn to use grep and find, two powerful command-line utilities, to search through and explore our codebase. Learn to search specific files and folders, using regular expressions to look for -- or ignore! -- particular phrases. We'll cover how to search recursively, get more context on your results, and some simple tricks to make your searches faster and more targeted.


Once you're familiar with grep and find, you'll be able to quickly answer questions such as: Do I use this function anywhere other than my tests? Where does this file get imported? Whether you're working on a new feature, reading a codebase for the first time, or refactoring existing code, grep and find can help you work faster and more effectively.

A Unix command used to search files for the occurrence of a string of characters that matches a specified pattern.

grep

Use Grep for Fast Search from the Command Line

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

***Note: RxJS imports have changed since the publication of this course. The concepts being taught on RxJS are still applicable.**

Angular has many built-in features for working closely with RxJS to help you build entirely reactive applications. This course will teach you how to use Angular with RxJS. We will learn how to use the ngrx/store library to manage state in a clean, reactive "Redux style."

This course assumes you've got a working knowledge of Angular and reactive programming with RxJS. If you don't, you might want to watch the following courses to get you up to speed! 
- [Get Started with Angular](https://egghead.io/courses/get-started-with-angular) 
- [Introduction to Reactive Programming with RxJS](
https://egghead.io/series/introduction-to-reactive-programming). 
- [Step by Step Async Programming with RxJS](https://egghead.io/series/step-by-step-async-javascript-with-rxjs) 
- [Getting Started With Redux](https://egghead.io/series/getting-started-with-redux), a course by Redux's, Dan Abramov.

We also have Intermediary Angular courses if you'd like to acquire more in-depth knowledge. 
- [Dependency Injection](https://egghead.io/courses/angular-2-dependency-injection-di-explained
- [Components, Directives](https://egghead.io/courses/building-angular-components)
- [Forms](https://egghead.io/courses/intro-to-angular-forms)
- [Router](https://egghead.io/courses/intro-to-angular-router)
- [Animating Web Apps](https://egghead.io/courses/animate-angular-web-applications)



Build Redux Style Applications with Angular, RxJS, and ngrx/store

When you have a bunch of text to sift through, standard Unix command line utilities like `grep`, `sed`, `awk`, `cut`, `sort`, and `uniq` can help extract the information you want. For example, with a git log for a project, you might want to group commits by day in order to see which days you're most productive, or find out how many commits you made last year. In this lesson, you'll learn how to combine these commands with the pipe operator to extract this data from git logs.

Analyze Git Logs with the Command Line

Reducers are also often used for changing a single property inside of other reducers. This lesson shows how a type can enter the people reducer, but then the people reducer can use a different type to call the clock reducer and get a value back.

Use a Reducer to Change an Object's Property Inside an Array

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

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

Sometimes you'll be looking for a string, but won't know which file it's in; or you'll want to find all usages of it within a directory. Learn how to use grep -r to recursively search all the files in a directory. 

Search directory contents recursively using grep

Learn how to use find to identify filenames matching specified patterns. We'll use find to identify all .jsx files in a directory, or all test files in a directory.

Use find to search for filename patterns

Learn to use git grep to only search through the tracked files in a git repo. This is especially useful when you want to exclude build artifacts or locally installed dependencies, such as webpack bundles or the node_modules directory. You'll also note that git grep is automatically colorized - we'll see how to get the same coloring effect with grep --color.

Search the contents of a git repository with git grep

By default, grep displays the file path and the line where a match is found. Learn to use the flags -A, -B, -C, and -n to get more context, and view line numbers as well as the lines surrounding a pattern match.


Show context around matches using grep

By using wildcards and glob patterns with the special characters . and *, you can create regular expressions that describe what kind of text you're looking for, instead of just plaintext strings. 

Search for basic patterns using grep

Learn to use grep's extended regular expressions to describe more complex patterns. The `?` and `+` special characters describe optional patterns. The `?` character matches zero or one instance of the preceding term, and the `+` character matches one or more instances of the preceding term. To use these characters, you'll need to either escape them with backslashes or turn on extended regular expressions with the `-E` flag.

Use grep's extended regular expressions to find complex patterns

Learn to use the special anchor characters `^` and `$` to indicate the beginning and end of lines when writing regular expressions for grep. These line anchors are part of basic regular expressions in grep, so you don't need to escape them.

Specify line beginning and end in patterns using grep

You can describe classes of characters using bracket expressions. We'll use expressions such as [a-zA-Z] and [0-9] to search for alphabetic and numeric characters with grep.

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