Learn Natural, Neo4j and Strapi

**Developers aren’t the only ones working on sites.** 

Marketers, copywriters, designers, and other non-coding roles all need to be able to make content changes. If you don't want to be bothered to open a PR every time a typo needs fixed, you *need* a CMS. 

And Strapi is an *amazing* CMS option.  

Strapi helps you quickly build a robust content API. You can host it yourself, it supports both RESTful and GraphQL, handles your authentication, lets you bring team members and it's highly customizable with plugins and extensions. 

You can take those gains even further by adding **Next.js 13 to the stack.** 

Next.js is fast, supports both server and client-side rendering, and features dynamic routes. Once you are generating dynamic pages from your CMS you’ll see just how powerful the combination of Strapi and Next.js is!

**In this course you will do the following:** 

- Building Content Models with Strapi
- Fetching Data from your Headless CMS
- Using React Server Components
- Using the Next.js App directory
- Setting up pagination in Strapi and Next.js
- Parsing and rendering content in your Next.js application
- Connecting external services to your Headless CMS (like Cloudinary for Media Management)
- Deploying your Next.js and Strapi Applications to a production environment
- Setting up and using Strapi Plugins
Transferring data between your Strapi environments

By the end of this course you’ll be building pages and managing your content like a pro!

strapi

Modern CMS Driven Web Applications with Strapi and Next 13

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

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

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

In this lesson, we’ll take a look at Natural’s phonetics feature. We’ll learn how to check whether two words sound alike, looking at both the SoundEx and Metaphone algorithms.

Check if words sound alike using Natural

This lesson introduces WordNet, which is an important resource in natural language processing. With WordNet, we can look up a word’s definition, or find its synonyms.

Find a word’s definition using WordNet in Natural

An important component of many natural language processing projects is being able to identify the grammar of a piece of text. We’ll learn how to do that with Natural’s parts of speech (POS) tagger.  

There are many tags, and it's worth looking them up online (search "POS tag symbols") to become familiar with them all. 

The setup of the tagger may seem a little strange, but it allows you to replace the lexicon or the rules with a different lexicon or rule set of your choice. 

Tag parts of speech using Natural

By this point we've seen that classification can take a long time, and with more data, it would take even longer. Luckily, Natural provides support to save your classifiers. In this lesson, we will learn how to save a classifier and load it into a new project in order to classify new data.

Using machine learning classifiers in a new project

A part of Natural Language Processing (NLP) is processing text by “tokenizing” language strings. This means we can break up a string of text into parts by word, sentence, etc. In this lesson, we will use the `natural` library to tokenize a string. First, we will break the string into words using `WordTokenizer`, `WordPunctTokenizer`, and `TreebankWordTokenizer`. Then we will break the string into sentences using `RegexpTokenizer`.

Break up language strings into parts using Natural

We'll start with the basics of creating a new Strapi project, naming the project API, and setting up the project to use an SQLite database.

Creating a New Strapi Project for Development with npx

The first thing we want to do is model the content that will be presented on our website. To do this we'll create a Post content type that will have several fields with types including text, rich text, date, and UID. 

After we create the content type you'll see how to manually create posts through the Strapi dashboard.

Create a Collection Type for a Post in Strapi

We have a problem right now in that if you were to try and fetch these posts from the API, you would get a 403 error. And that's because we haven't set up the end user permissions for the API to be able to access this content. So let's go ahead and do that now.

We'll modify the User permissions for the `Post` role and give public access to `find` and `findOne`.

Set up API End User Permissions to Make REST Queries in Strapi

GraphQL is a powerful technology that lets you query the exact data that you need when you need it on your front end. Strapi allows for GraphQL integration through a plugin.

You can install GraphQL with the following command:

```bash
yarn strapi install graphql
```
You'll notice this adds GraphQL in your plugins tab within Strapi. 

When that is installed you can navigate to `/graphql` in your Strapi project and query the data you have. 

Install and Query GraphQL API in Strapi

We'll cover the basics of building a new page in Next.js, specifically an "About Us" page. If you've used Next before, this will feel very similar to creating a new page in the `pages` directory. 

While doing this we will also be introduced to some of the components that come with the template, such as the `PageContainer`, `Main`, `Title`, and `Description` components which you can check out [in more detail here](https://github.com/malgamves/next-13-website-template/tree/main/components).


Create an About Us Page inside the Next.js 13 App Directory

SolidStart is a JavaScript Framework designed to build full-stack SolidJS apps and enhance your developer experience.

In this course, you will learn how to:
- Set up a SolidStart project
- Toggle different rendering modes
- Leverage file system routing to turn your files into routes
- Create API routes to expose some public endpoints
- Fetch, prefetch, update and cache your data
- Turn your functions and actions into server-executing ones
- Get rid of unnecessary network waterfalls by using Single Flight Mutations.

After this course, you should be able to leverage SolidStart to build your Solid applications.

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

SolidStart is a JavaScript Framework designed to build full-stack SolidJS apps and enhance your developer experience.

In this course, you will learn how to:
- Set up a SolidStart project
- Toggle different rendering modes
- Leverage file system routing to turn your files into routes
- Create API routes to expose some public endpoints
- Fetch, prefetch, update and cache your data
- Turn your functions and actions into server-executing ones
- Get rid of unnecessary network waterfalls by using Single Flight Mutations.

Getting Started with SolidStart

Bootstrap is an incredibly popular CSS framework designed to make your website look great on mobile and desktop.

By the end of this course, you'll be familiar with many of the popular classes and components that Bootstrap uses to apply in your own projects.

For each feature you build in the course, you'll get a sense for what the relevant classes do for those components and links to documentation for further exploration.

For the course demo application, we will analyze the landing pages of Microsoft and Apple to identify common components that are implemented. When these are identified, you'll implement these components yourself with Bootstrap.

You'll build several common UI elements such as a nav bar, a carousel of images, Cards, and Forms.

Through building these components, you'll understand what is behind the different classes Bootstrap gives you and get familiar with how it exposes flex and grid layout for you.

Cascading Style Sheets bring order and beauty to our applications.

Create Professional Responsive Websites using Bootstrap

This course is perfect for those looking for a lightweight alternative to NgRx Store that scales effortlessly.

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.

Scalable Signals Angular Architecture with NGRX Signal Store

Learn how the latest JavaScript features can help you improve your codebase. 

Learn the Latest ECMAScript Features (ES2024, ES2023, ...)

course repository: https://github.com/ducin/egghead-typescript/tree/brand-types-value-objects

TypeScript is a typed superset of JavaScript that compiles to plain JavaScript.

typescript

Domain Data Modelling using TypeScript Aliases, Brand Types and Value Objects

**Note:** This course is being actively developed and more lessons will be added in the future.

Cursor is an AI-enhnaced code editor that allows you to call upon the robots to refactor or stub out functions for you with natural language. 

In this course, John will show you workflows that will save you time and effort by utilizing the features such as its mult-line editing and context.

In particular, by giving Cursor's AI the proper context, whether that's lines of code or multiple files, you'll get better output when trying to extend or refactor logic that's present.


Bite-size video tutorials for badass web developers.

egghead

Productive Developer Workflows with AI Enhanced Cursor IDE

Learn the fundamentals of React Query by going through the basic API and then implementing search in an employee tracking app.

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

react

Simplify State Management with React Query

Vue (pronounced /vjuː/, like view) is a progressive framework for building user interfaces. Unlike other monolithic frameworks, Vue is designed from the ground up to be incrementally adoptable. The core library is focused on the view layer only, and is very easy to pick up and integrate with other libraries or existing projects. On the other hand, Vue is also perfectly capable of powering sophisticated Single-Page Applications when used in combination with modern tooling and supporting libraries.

Create Interactive 3D Experiences with TresJS

You've seen that Angular signals are here, and know that signal-components are coming up.

This marks a paradigm-shift towards reactive programming in Angular.

Are you ready?

What if you could start learning signals and feel pleased with your progress? And reach a point where you feel confident when using signals in production?

And feel ready when signal-based components come?

Changes are coming, and you can get ahead of them.

By taking this cousre you will learn how to:

- Create computed signals
- Share your signals in services
- Use and cleanup signal effects
- Turn signals into observables and vice versa
- ... and more

In 52 minutes over the course of 20 bite-sized lessons, you'll learn everything you need to know to take advantage of signals now and be prepared for signal-based components!

angular

Modernize State Management in Angular with Signals

Get started with Supabase on your machine

Supabase is an open source Firebase alternative. A service to:

- Listen to database changes.
- Query your tables, including filtering, pagination, and deeply nested relationships (like GraphQL).
- Create, update, and delete rows.
- Manage your users and their permissions.
- Interact with your database using a simple UI.

Supabase is not a 1-to-1 mapping of Firebase. Most notably, Supabase uses Postgres rather than a NoSQL store. 

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