MonkeyLearn is a text analysis platform that helps you identify and extract actionable data from a variety of raw texts, including emails, chats, webpages, papers, tweets, and more! You can use custom tags to categorize texts, such as sentiments or topics, and extract specific data, such as organizations or keywords.
Netlify is the platform your developers love for building highly-performant and dynamic web sites, e-commerce stores and applications.
Netlify IntegrationsNetlify + Monkey Learn
Classify Text in monkeylearn when New Deploy Succeeded is created in Netlify Read More...Netlify + Monkey Learn
Extract Text in monkeylearn when New Deploy Succeeded is created in Netlify Read More...Netlify + Monkey Learn
Upload training Data in monkeylearn when New Deploy Succeeded is created in Netlify Read More...Netlify + Monkey Learn
Classify Text in monkeylearn when New Deploy Failed is created in Netlify Read More...Netlify + Monkey Learn
Extract Text in monkeylearn when New Deploy Failed is created in Netlify Read More...It's easy to connect Monkey Learn + Netlify without coding knowledge. Start creating your own business flow.
Triggers when a new deploy of your site has failed.
Triggers when a new deploy of your site has started building.
Triggers when a new version of your site has successfully deployed.
Triggers when a form receives a new submission.
Classifies texts with a given classifier.
Extracts information from texts with a given extractor.
Uploads data to a classifier.
Performs a new deploy of an existing site.
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MonkeyLearn is a machine learning top that supports Natural Language Processing, NLP, and Text Analytics. The top was started in 2013 by Juan Pablo Buritica with the goal of democratizing natural language processing. It has achieved this by making machine learning accessible to developers, analysts, data scientists, and anyone interested in creating intelligent applications.
Netlify is an online static web host for static websites. Netlify is known for its speed, ease of use, and automated deployment features. This makes it preferable to other static website hosts, such as GitHub Pages.
Netlify is a static site hosting service that can be used with any static site generator. A static site generator is a piece of software that creates static HTML files from a dynamic database or API. In order to make a site with Netlify, the developer must first create a site with a static site generator.
Before Netlify can be used for a site created with a static site generator, the developer must upload the content to the site. This can be done using a command line interface, command line tops, or a third-party plugin for their static site generator.
After uploading the content, the developer must configure Netlify to build the site by adding a build command to a file called netlify.toml . The build command can be added via the command line interface or by creating a plugin for their static site generator. Once configured, Netlify will automatically deploy any changes made to the static website, as long as it’s within the parameters of the build command. For example, if the developer adds HTML to a page of their static website and saves it through their IDE, Netlify will automatically build and deploy the changes. If the developer wanted to add an image to an article on their blog and save it through their IDE, Netlify would not build and deploy the changes because they were not made to the proper file type (HTML. This process streamlines the development process because developers don’t have to manually push updates to their sites; they only have to make changes and save them.
Content management systems like Wordpress and Drupal allow users to create and manage content without having to know HTML. A user can create a page by clicking on “Pages” in their dashboard and then clicking on “Add New Page” and fill out the form and save it. This creates an HTML file that can be edited and saved through an editor like Microsoft Word or Google Docs. An HTML file for this would look something like this:
<!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width"> <link rel="stylesheet" rel="nofollow" href="https:/etdna.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css"> <title>My New Page</title> </head> <body> Here is my new content </body> </html> 1 2 3 4 5 6 7 8 9 10 11 < ! DOCTYPE html > < html lang = "en" > < head > < meta charset = "utf-8" > < meta name = "viewport" content = "width=device-width" > < link rel = "stylesheet" rel="nofollow" href= "https:/etdna.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css" > < title > My New Page < / title > < / head > < body > Here is my new content < / body > < / html >
This is fine if there are only one or two pages on a website but what happens when there are hundreds or thousands of pages on a website? Managing these pages becomes unmanageable without help from another system. That’s where CMSs come into play. Content management systems are systems that allow users to create, edit, delete, and manage large amounts of content (text, images, videos, etc.. These systems can be built using different technpogies like PHP, NodeJS, Python, Ruby, etc., but any technpogy can be used as long as it is compatible with Netlify’s build commands. One way to work around this incompatibility issue is by using one technpogy (NodeJS. to create the CMS and another (Wordpress. to provide the front end functionality (such as displaying posts. To do this, the developer would use NodeJS to create the CMS that manages all of the data for posts, pages, users, etc., then use Wordpress to display them on the website. When someone visits the website, they will see HTML files generated by Wordpress rather than HTML files generated by NodeJS so there isn’t any confusion between how someone accesses information because they are served by different technpogies. The problem with this approach is that Wordpress does not support plugins for NLP so if someone wants to use NLP on their website they must either develop their own plugin or use an outside service like MonkeyLearn or IBM Watson. Since developing plugins can be time consuming and expensive, most developers just use outside services like MonkeyLearn or IBM Watson which brings us to our next section…
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