Nikunj Shah

Nikunj Shah

1574214892

Getting started with Natural Language Processing using Node.js

Introduction

The internet facilitates a never-ending creation of large volumes of unstructured textual data. Luckily, we have modern systems that can make sense of this kind of data.

Modern computer systems can make sense of natural languages using an underlying technology called NLP (natural language processing). This technology can process human language as input and perform one or more of the following operations:

  • Sentiment analysis (Is it a positive or negative statement?)
  • Topic classification (What is it about?)
  • Decide on what actions should be taken based on this statement
  • Intent extraction (What is the intention behind this statement?)

Natural language processing (NLP) is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.

Significant implementations of NLP aren’t too far from us these days as most of our devices integrate AI (artificial intelligence), ML (machine learning) and NLP to enhance human-to-machine communications. Here are some common examples of NLP in action:

  1. Search engines: One of the most helpful technologies is the Google Search engine. You put in text and receive millions of related results as a response. This is possible because of the NLP technology that can make sense of the input and perform a series of logical operations. This is also what allows Google Search to understand your intent and suggest the proper spelling to you when you spell a search term incorrectly.
  2. Intelligent virtual assistants: Virtual assistants such as Siri, Alexa, and Google Assistant show an advanced level of the implementation of NLP. After receiving verbal input from you, they can identify the intent, perform an operation and send back a response in a natural language.
  3. Smart chatbots: Chatbots can analyze large amounts of textual data and give different responses based on large data and their ability to detect intent. This gives the overall feel of a natural conversation and not one with a machine.
  4. Spam filter: Have you noticed that email clients are constantly getting better at filtering spam emails out of your inbox? This is possible because the filter engines can understand the content of emails — mostly using Bayesian spam filtering — and decide if it’s spam or not.

The use cases above show that AI, ML, and NLP are already being used heavily on the web. Since humans interact with websites using natural languages, we should build our websites with NLP capabilities.

Python is usually the go-to language when the topic is NLP (or ML and AI) because of its wealth of language processing packages like Natural Language Toolkit. However, JavaScript is growing rapidly and the existence of NPM (Node Package Manager) gives its developers access to a large number of packages, including packages to perform NLP for different languages.

In this article, we will focus on getting started with NLP using Node. We will be using a JavaScript library called natural. By adding the natural library to our project, our code will be able to parse, interpret, manipulate, and understand natural languages from user input.

This article will barely scratch the surface of NLP. This post will be useful for developers who already use NLP with Python but want to transition to achieve the same results with Node. Complete newbies will also learn a lot about NLP as a technology and its usage with Node.

Prerequisite

  1. Basic knowledge of Node.js
  2. A system that is set up to run Node code

To code along with this article, you will need to create an index.js file and paste in the snippet you want to try then run the file with Node.

Let’s begin.

Installation

We can install natural by running the following command:

npm install natural

The source code to each of the following usage examples in the next section is available on Github. Feel free to clone it, fork it or submit an issue.

Usage

Let’s learn how to perform some basic but important NLP tasks using natural.

Tokenization

Tokenization is the process of demarcating and possibly classifying sections of a string of input characters. The resulting tokens are then passed on to some other form of processing. The process can be considered a sub-task of parsing input.

For example, in the text string: The quick brown fox jumps over the lazy dog

The string isn’t implicitly segmented on spaces, as a natural language speaker would do. The raw input, the 43 characters, must be explicitly split into the 9 tokens with a given space delimiter (i.e., matching the string " " or regular expression /\s{1}/).

Natural ships with a number of smart tokenizer algorithms that can break text into arrays of tokens. Here’s a code snippet showing the usage of the Word tokenizer:

// index.js

var natural = require('natural');
var tokenizer = new natural.WordTokenizer();

console.log(tokenizer.tokenize("The quick brown fox jumps over the lazy dog"));

Running this with Node gives the following output:

[ 'The',
  'quick',
  'brown',
  'fox',
  'jumps',
  'over',
  'the',
  'lazy',
  'dog' ]

Stemming

Stemming refers to the reduction of words to their word stem (also known as base or root form). For example, words such as cats, catlike, and catty will be stemmed down to the root word — cat.

Natural currently supports two stemming algorithms — Porter and Lancaster (Paice/Husk). Here’s a code snippet implementing stemming, using the Porter algorithm:

// index.js

var natural = require('natural');

natural.PorterStemmer.attach();
console.log("I can see that we are going to be friends".tokenizeAndStem());

This example uses the attach() method to patch stem() and tokenizeAndStem() to String as a shortcut to PorterStemmer.stem(token).tokenizeAndStem(). The result is the breaking down of the text into single words then an array of stemmed tokens will be returned:

[ 'go', 'friend' ]

Note: In the result above, stop words have been removed by the algorithm. Stop words are words that are filtered out before the processing of natural language(for example be, an, and to are all stop words).

Measuring the similarity between words (string distance)

Natural provides an implementation of four algorithms for calculating string distance, Hamming distance, Jaro-Winkler, Levenshtein distance, and Dice coefficient. Using these algorithms, we can tell if two strings match or not. For the sake of this project we will be using Hamming distance.

Hamming distance measures the distance between two strings of equal length by counting the number of different characters. The third parameter indicates whether the case should be ignored. By default, the algorithm is case sensitive.

Here’s a code snippet showing the usage of the Hemming algorithm for calculating string distance:

// index.js

var natural = require('natural');

console.log(natural.HammingDistance("karolin", "kathrin", false));
console.log(natural.HammingDistance("karolin", "kerstin", false));
console.log(natural.HammingDistance("short string", "longer string", false));

The output:

3
3
-1

The first two comparisons return 3 because three letters differ. The last one returns -1 because the lengths of the strings being compared are different.

Classification

Text classification also known as text tagging is the process of classifying text into organized groups. That is, if we have a new unknown statement, our processing system can decide which category it fits in the most based on its content.

Some of the most common use cases for automatic text classification include the following:

  • Sentiment analysis
  • Topic detection
  • Language detection

Natural currently supports two classifiers — Naive Bayes and logistic regression. The following examples use the BayesClassifier class:

// index.js

var natural = require('natural');

var classifier = new natural.BayesClassifier();
classifier.addDocument('i am long qqqq', 'buy');
classifier.addDocument('buy the q\'s', 'buy');
classifier.addDocument('short gold', 'sell');
classifier.addDocument('sell gold', 'sell');
classifier.train();

console.log(classifier.classify('i am short silver'));
console.log(classifier.classify('i am long copper'));

In the code above, we trained the classifier on sample text. It will use reasonable defaults to tokenize and stem the text. Based on the sample text, the console will log the following output:

sell
buy

Sentiment analysis

Sentiment analysis (also known as opinion mining or emotion AI) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.

Natural supports algorithms that can calculate the sentiment of each piece of text by summing the polarity of each word and normalizing it with the length of the sentence. If a negation occurs the result is made negative.

Here’s an example of its usage:

// index.js

var natural = require('natural');
var Analyzer = natural.SentimentAnalyzer;
var stemmer = natural.PorterStemmer;
var analyzer = new Analyzer("English", stemmer, "afinn");

// getSentiment expects an array of strings
console.log(analyzer.getSentiment(["I", "don't", "want", "to", "play", "with", "you"]));

The constructor has three parameters:

  • Language
  • Stemmer- to increase the coverage of the sentiment analyzer a stemmer may be provided
  • Vocabulary- sets the type of vocabulary, "afinn", "senticon" or "pattern" are valid values

Running the code above gives the following output:

0.42857142857142855 // indicates a relatively negative statement

Phonetic matching

Using natural, we can compare two words that are spelled differently but sound similar using phonetic matching. Here’s an example using the metaphone.compare() method:

// index.js

var natural = require('natural');
var metaphone = natural.Metaphone;
var soundEx = natural.SoundEx;

var wordA = 'phonetics';
var wordB = 'fonetix';

if (metaphone.compare(wordA, wordB))
    console.log('They sound alike!');

// We can also obtain the raw phonetics of a word using process()
console.log(metaphone.process('phonetics'));

We also obtained the raw phonetics of a word using process(). We get the following output when we run the code above:

They sound alike!
FNTKS

Spell check

Users may make typographical errors when supplying input to a web application through a search bar or an input field. Natural has a probabilistic spellchecker that can suggest corrections for misspelled words using an array of tokens from a text corpus.

Let’s explore an example using an array of two words (also known as a corpus) for simplicity:

// index.js

var natural = require('natural');

var corpus = ['something', 'soothing'];
var spellcheck = new natural.Spellcheck(corpus);

console.log(spellcheck.getCorrections('soemthing', 1)); 
console.log(spellcheck.getCorrections('soemthing', 2));

It suggests corrections (sorted by probability in descending order) that are up to a maximum edit distance away from the input word. A maximum distance of 1 will cover 80% to 95% of spelling mistakes. After a distance of 2, it becomes very slow.

We get the following output from running the code:

[ 'something' ]
[ 'something', 'soothing' ]

Conclusion

Here’s a quick summary of what we’ve learned so far in this article:

  • Computer systems are getting smarter by the day and can extract meaning from large volumes of unstructured textual data using NLP
  • Python has a wealth of intelligent packages for performing AI, ML, and NLP tasks but JavaScript is growing really rapidly and its package manager has an impressive number of packages capable of processing natural language
  • Natural, a JavaScript package, is robust in performing NLP operations and has a number of algorithm alternatives for each task

The source code to each of the following usage examples in the next section is available on Github. Feel free to clone it, fork it or submit an issue.

#nodejs #node #javascript #machine-learning #data-science

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Buddha Community

Getting started with Natural Language Processing using Node.js

NBB: Ad-hoc CLJS Scripting on Node.js

Nbb

Not babashka. Node.js babashka!?

Ad-hoc CLJS scripting on Node.js.

Status

Experimental. Please report issues here.

Goals and features

Nbb's main goal is to make it easy to get started with ad hoc CLJS scripting on Node.js.

Additional goals and features are:

  • Fast startup without relying on a custom version of Node.js.
  • Small artifact (current size is around 1.2MB).
  • First class macros.
  • Support building small TUI apps using Reagent.
  • Complement babashka with libraries from the Node.js ecosystem.

Requirements

Nbb requires Node.js v12 or newer.

How does this tool work?

CLJS code is evaluated through SCI, the same interpreter that powers babashka. Because SCI works with advanced compilation, the bundle size, especially when combined with other dependencies, is smaller than what you get with self-hosted CLJS. That makes startup faster. The trade-off is that execution is less performant and that only a subset of CLJS is available (e.g. no deftype, yet).

Usage

Install nbb from NPM:

$ npm install nbb -g

Omit -g for a local install.

Try out an expression:

$ nbb -e '(+ 1 2 3)'
6

And then install some other NPM libraries to use in the script. E.g.:

$ npm install csv-parse shelljs zx

Create a script which uses the NPM libraries:

(ns script
  (:require ["csv-parse/lib/sync$default" :as csv-parse]
            ["fs" :as fs]
            ["path" :as path]
            ["shelljs$default" :as sh]
            ["term-size$default" :as term-size]
            ["zx$default" :as zx]
            ["zx$fs" :as zxfs]
            [nbb.core :refer [*file*]]))

(prn (path/resolve "."))

(prn (term-size))

(println (count (str (fs/readFileSync *file*))))

(prn (sh/ls "."))

(prn (csv-parse "foo,bar"))

(prn (zxfs/existsSync *file*))

(zx/$ #js ["ls"])

Call the script:

$ nbb script.cljs
"/private/tmp/test-script"
#js {:columns 216, :rows 47}
510
#js ["node_modules" "package-lock.json" "package.json" "script.cljs"]
#js [#js ["foo" "bar"]]
true
$ ls
node_modules
package-lock.json
package.json
script.cljs

Macros

Nbb has first class support for macros: you can define them right inside your .cljs file, like you are used to from JVM Clojure. Consider the plet macro to make working with promises more palatable:

(defmacro plet
  [bindings & body]
  (let [binding-pairs (reverse (partition 2 bindings))
        body (cons 'do body)]
    (reduce (fn [body [sym expr]]
              (let [expr (list '.resolve 'js/Promise expr)]
                (list '.then expr (list 'clojure.core/fn (vector sym)
                                        body))))
            body
            binding-pairs)))

Using this macro we can look async code more like sync code. Consider this puppeteer example:

(-> (.launch puppeteer)
      (.then (fn [browser]
               (-> (.newPage browser)
                   (.then (fn [page]
                            (-> (.goto page "https://clojure.org")
                                (.then #(.screenshot page #js{:path "screenshot.png"}))
                                (.catch #(js/console.log %))
                                (.then #(.close browser)))))))))

Using plet this becomes:

(plet [browser (.launch puppeteer)
       page (.newPage browser)
       _ (.goto page "https://clojure.org")
       _ (-> (.screenshot page #js{:path "screenshot.png"})
             (.catch #(js/console.log %)))]
      (.close browser))

See the puppeteer example for the full code.

Since v0.0.36, nbb includes promesa which is a library to deal with promises. The above plet macro is similar to promesa.core/let.

Startup time

$ time nbb -e '(+ 1 2 3)'
6
nbb -e '(+ 1 2 3)'   0.17s  user 0.02s system 109% cpu 0.168 total

The baseline startup time for a script is about 170ms seconds on my laptop. When invoked via npx this adds another 300ms or so, so for faster startup, either use a globally installed nbb or use $(npm bin)/nbb script.cljs to bypass npx.

Dependencies

NPM dependencies

Nbb does not depend on any NPM dependencies. All NPM libraries loaded by a script are resolved relative to that script. When using the Reagent module, React is resolved in the same way as any other NPM library.

Classpath

To load .cljs files from local paths or dependencies, you can use the --classpath argument. The current dir is added to the classpath automatically. So if there is a file foo/bar.cljs relative to your current dir, then you can load it via (:require [foo.bar :as fb]). Note that nbb uses the same naming conventions for namespaces and directories as other Clojure tools: foo-bar in the namespace name becomes foo_bar in the directory name.

To load dependencies from the Clojure ecosystem, you can use the Clojure CLI or babashka to download them and produce a classpath:

$ classpath="$(clojure -A:nbb -Spath -Sdeps '{:aliases {:nbb {:replace-deps {com.github.seancorfield/honeysql {:git/tag "v2.0.0-rc5" :git/sha "01c3a55"}}}}}')"

and then feed it to the --classpath argument:

$ nbb --classpath "$classpath" -e "(require '[honey.sql :as sql]) (sql/format {:select :foo :from :bar :where [:= :baz 2]})"
["SELECT foo FROM bar WHERE baz = ?" 2]

Currently nbb only reads from directories, not jar files, so you are encouraged to use git libs. Support for .jar files will be added later.

Current file

The name of the file that is currently being executed is available via nbb.core/*file* or on the metadata of vars:

(ns foo
  (:require [nbb.core :refer [*file*]]))

(prn *file*) ;; "/private/tmp/foo.cljs"

(defn f [])
(prn (:file (meta #'f))) ;; "/private/tmp/foo.cljs"

Reagent

Nbb includes reagent.core which will be lazily loaded when required. You can use this together with ink to create a TUI application:

$ npm install ink

ink-demo.cljs:

(ns ink-demo
  (:require ["ink" :refer [render Text]]
            [reagent.core :as r]))

(defonce state (r/atom 0))

(doseq [n (range 1 11)]
  (js/setTimeout #(swap! state inc) (* n 500)))

(defn hello []
  [:> Text {:color "green"} "Hello, world! " @state])

(render (r/as-element [hello]))

Promesa

Working with callbacks and promises can become tedious. Since nbb v0.0.36 the promesa.core namespace is included with the let and do! macros. An example:

(ns prom
  (:require [promesa.core :as p]))

(defn sleep [ms]
  (js/Promise.
   (fn [resolve _]
     (js/setTimeout resolve ms))))

(defn do-stuff
  []
  (p/do!
   (println "Doing stuff which takes a while")
   (sleep 1000)
   1))

(p/let [a (do-stuff)
        b (inc a)
        c (do-stuff)
        d (+ b c)]
  (prn d))
$ nbb prom.cljs
Doing stuff which takes a while
Doing stuff which takes a while
3

Also see API docs.

Js-interop

Since nbb v0.0.75 applied-science/js-interop is available:

(ns example
  (:require [applied-science.js-interop :as j]))

(def o (j/lit {:a 1 :b 2 :c {:d 1}}))

(prn (j/select-keys o [:a :b])) ;; #js {:a 1, :b 2}
(prn (j/get-in o [:c :d])) ;; 1

Most of this library is supported in nbb, except the following:

  • destructuring using :syms
  • property access using .-x notation. In nbb, you must use keywords.

See the example of what is currently supported.

Examples

See the examples directory for small examples.

Also check out these projects built with nbb:

API

See API documentation.

Migrating to shadow-cljs

See this gist on how to convert an nbb script or project to shadow-cljs.

Build

Prequisites:

  • babashka >= 0.4.0
  • Clojure CLI >= 1.10.3.933
  • Node.js 16.5.0 (lower version may work, but this is the one I used to build)

To build:

  • Clone and cd into this repo
  • bb release

Run bb tasks for more project-related tasks.

Download Details:
Author: borkdude
Download Link: Download The Source Code
Official Website: https://github.com/borkdude/nbb 
License: EPL-1.0

#node #javascript

Aria Barnes

Aria Barnes

1622719015

Why use Node.js for Web Development? Benefits and Examples of Apps

Front-end web development has been overwhelmed by JavaScript highlights for quite a long time. Google, Facebook, Wikipedia, and most of all online pages use JS for customer side activities. As of late, it additionally made a shift to cross-platform mobile development as a main technology in React Native, Nativescript, Apache Cordova, and other crossover devices. 

Throughout the most recent couple of years, Node.js moved to backend development as well. Designers need to utilize a similar tech stack for the whole web project without learning another language for server-side development. Node.js is a device that adjusts JS usefulness and syntax to the backend. 

What is Node.js? 

Node.js isn’t a language, or library, or system. It’s a runtime situation: commonly JavaScript needs a program to work, however Node.js makes appropriate settings for JS to run outside of the program. It’s based on a JavaScript V8 motor that can run in Chrome, different programs, or independently. 

The extent of V8 is to change JS program situated code into machine code — so JS turns into a broadly useful language and can be perceived by servers. This is one of the advantages of utilizing Node.js in web application development: it expands the usefulness of JavaScript, permitting designers to coordinate the language with APIs, different languages, and outside libraries.

What Are the Advantages of Node.js Web Application Development? 

Of late, organizations have been effectively changing from their backend tech stacks to Node.js. LinkedIn picked Node.js over Ruby on Rails since it took care of expanding responsibility better and decreased the quantity of servers by multiple times. PayPal and Netflix did something comparative, just they had a goal to change their design to microservices. We should investigate the motivations to pick Node.JS for web application development and when we are planning to hire node js developers. 

Amazing Tech Stack for Web Development 

The principal thing that makes Node.js a go-to environment for web development is its JavaScript legacy. It’s the most well known language right now with a great many free devices and a functioning local area. Node.js, because of its association with JS, immediately rose in ubiquity — presently it has in excess of 368 million downloads and a great many free tools in the bundle module. 

Alongside prevalence, Node.js additionally acquired the fundamental JS benefits: 

  • quick execution and information preparing; 
  • exceptionally reusable code; 
  • the code is not difficult to learn, compose, read, and keep up; 
  • tremendous asset library, a huge number of free aides, and a functioning local area. 

In addition, it’s a piece of a well known MEAN tech stack (the blend of MongoDB, Express.js, Angular, and Node.js — four tools that handle all vital parts of web application development). 

Designers Can Utilize JavaScript for the Whole Undertaking 

This is perhaps the most clear advantage of Node.js web application development. JavaScript is an unquestionable requirement for web development. Regardless of whether you construct a multi-page or single-page application, you need to know JS well. On the off chance that you are now OK with JavaScript, learning Node.js won’t be an issue. Grammar, fundamental usefulness, primary standards — every one of these things are comparable. 

In the event that you have JS designers in your group, it will be simpler for them to learn JS-based Node than a totally new dialect. What’s more, the front-end and back-end codebase will be basically the same, simple to peruse, and keep up — in light of the fact that they are both JS-based. 

A Quick Environment for Microservice Development 

There’s another motivation behind why Node.js got famous so rapidly. The environment suits well the idea of microservice development (spilling stone monument usefulness into handfuls or many more modest administrations). 

Microservices need to speak with one another rapidly — and Node.js is probably the quickest device in information handling. Among the fundamental Node.js benefits for programming development are its non-obstructing algorithms.

Node.js measures a few demands all at once without trusting that the first will be concluded. Many microservices can send messages to one another, and they will be gotten and addressed all the while. 

Versatile Web Application Development 

Node.js was worked in view of adaptability — its name really says it. The environment permits numerous hubs to run all the while and speak with one another. Here’s the reason Node.js adaptability is better than other web backend development arrangements. 

Node.js has a module that is liable for load adjusting for each running CPU center. This is one of numerous Node.js module benefits: you can run various hubs all at once, and the environment will naturally adjust the responsibility. 

Node.js permits even apportioning: you can part your application into various situations. You show various forms of the application to different clients, in light of their age, interests, area, language, and so on. This builds personalization and diminishes responsibility. Hub accomplishes this with kid measures — tasks that rapidly speak with one another and share a similar root. 

What’s more, Node’s non-hindering solicitation handling framework adds to fast, letting applications measure a great many solicitations. 

Control Stream Highlights

Numerous designers consider nonconcurrent to be one of the two impediments and benefits of Node.js web application development. In Node, at whatever point the capacity is executed, the code consequently sends a callback. As the quantity of capacities develops, so does the number of callbacks — and you end up in a circumstance known as the callback damnation. 

In any case, Node.js offers an exit plan. You can utilize systems that will plan capacities and sort through callbacks. Systems will associate comparable capacities consequently — so you can track down an essential component via search or in an envelope. At that point, there’s no compelling reason to look through callbacks.

 

Final Words

So, these are some of the top benefits of Nodejs in web application development. This is how Nodejs is contributing a lot to the field of web application development. 

I hope now you are totally aware of the whole process of how Nodejs is really important for your web project. If you are looking to hire a node js development company in India then I would suggest that you take a little consultancy too whenever you call. 

Good Luck!

Original Source

#node.js development company in india #node js development company #hire node js developers #hire node.js developers in india #node.js development services #node.js development

Hire Dedicated Node.js Developers - Hire Node.js Developers

If you look at the backend technology used by today’s most popular apps there is one thing you would find common among them and that is the use of NodeJS Framework. Yes, the NodeJS framework is that effective and successful.

If you wish to have a strong backend for efficient app performance then have NodeJS at the backend.

WebClues Infotech offers different levels of experienced and expert professionals for your app development needs. So hire a dedicated NodeJS developer from WebClues Infotech with your experience requirement and expertise.

So what are you waiting for? Get your app developed with strong performance parameters from WebClues Infotech

For inquiry click here: https://www.webcluesinfotech.com/hire-nodejs-developer/

Book Free Interview: https://bit.ly/3dDShFg

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Node JS Development Company| Node JS Web Developers-SISGAIN

Top organizations and start-ups hire Node.js developers from SISGAIN for their strategic software development projects in Illinois, USA. On the off chance that you are searching for a first rate innovation to assemble a constant Node.js web application development or a module, Node.js applications are the most appropriate alternative to pick. As Leading Node.js development company, we leverage our profound information on its segments and convey solutions that bring noteworthy business results. For more information email us at hello@sisgain.com

#node.js development services #hire node.js developers #node.js web application development #node.js development company #node js application

sophia tondon

sophia tondon

1625114985

Top 10 NodeJs app Development Companies- ValueCoders

Node.js is a prominent tech trend in the space of web and mobile application development. It has been proven very efficient and useful for a variety of application development. Thus, all business owners are eager to leverage this technology for creating their applications.

Are you striving to develop an application using Node.js? But can’t decide which company to hire for NodeJS app development? Well! Don’t stress over it, as the following list of NodeJS app development companies is going to help you find the best partner.

Let’s take a glance at top NodeJS application development companies to hire developers in 2021 for developing a mind-blowing application solution.

Before enlisting companies, I would like to say that every company has a foundation on which they thrive. Their end goals, qualities, and excellence define their competence. Thus, I prepared this list by considering a number of aspects. While making this list, I have considered the following aspects:

  • Review and rating
  • Enlisted by software peer & forums
  • Hourly price
  • Offered services
  • Year of experience (Average 8+ years)
  • Credibility & Excellence
  • Served clients and more

I believe this list will help you out in choosing the best NodeJS service provider company. So, now let’s explore the top NodeJS developer companies to choose from in 2021.

#1. JSGuru

JSGuru is a top-rated NodeJS app development company with an innovative team of dedicated NodeJS developers engaged in catering best-class UI/UX design, software products, and AWS professional services.

It is a team of one of the most talented developers to hire for all types of innovative solution development, including social media, dating, enterprise, and business-oriented solutions. The company has worked for years with a number of startups and launched a variety of products by collaborating with big-name corporations like T-systems.

If you want to hire NodeJS developers to secure an outstanding application, I would definitely suggest them. They serve in the area of eLearning, FinTech, eCommerce, Telecommunications, Mobile Device Management, and more.

  • Ratings: 4.9/5.0

  • Founded: 2006

  • Headquarters: Banja Luka, Bosnia, and Herzegovina

  • Price: Starting from $50/hour

Visit Website - https://www.valuecoders.com/blog/technology-and-apps/top-node-js-app-development-companies

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