Changing technologies in the software industry have impacted the services being facilitated. Mobile applications are rapidly replacing normal websites by providing better user experience and ease of usability by offering services on smartphones and smart devices. Hence, the market has changed, but technologies like JavaScript are still in the field, supporting the innovative approaches and newer trends of the market. As the requirement for automation is becoming the top trend in the market, Machine learning and artificial intelligence are once again popular in the market and the development in these domains is increasing by leaps and bounces.
What is Machine Learning?
Machine Learning is a subdomain of Artificial Intelligence which includes the study of how to make machines learn and adapt to newer things or knowledge that too automatically. Hence, Machine Learning is about enabling the machines to feed data to themselves only (automatically) and this knowledge can be used to generate better outputs and predict outcomes of processes. Therefore, Machine Learning (ML) plays a vital role in making a system intelligent and sits in the top trends of the industry.
How NodeJS Fit in?
NodeJS is a framework that supports running the JavaScript coded applications to run without needing the browser. Offering lightweight and excellent support for developing event-driven applications, NodeJS has emerged as one of the trending technologies itself and has attracted many with their support through the libraries they offer to facilitate easier and faster programming. As JavaScript and NodeJS have now not just remained the web technologies, they are being used for various purposes and Machine Learning is one of them.
Providing excellent support through the libraries it includes, NodeJS establishes itself as a framework to use for developing Machine Learning based applications. Here is the list of such applications that extend their great support at developing Machine Learning supportive JavaScript code.
ml.js
This library has been developed by the mljs organization and is available on Github for use. It includes various concerns of Machine Learning like Regression, K-Means clustering, Neural networks, and many more as different categories containing a huge number of libraries falling in each category separately. It includes support for all the data mining tasks and supports browser-based runtime. However, for supporting the Node.js environment, it includes a separate npm package to be used too. As all the packages and libraries are sectioned very wisely, only required libraries are to be installed and used to save storage space and ensure faster execution.
Brain.js
A library dedicated to supporting artificial neural network operations, Brain.js is one of the important libraries for implementing Machine Learning as it extends the support through running in web browsers and Node.js environments. An artificial neural network is associated with possessing complex mathematical formulas and problems but Brain.js makes the work easier by facilitating the common functions in the library itself to allow faster development of Machine Learning code.
Synaptic
One more library supporting artificial neural networks, Synaptic is a JavaScript-based platform that extends the support by including the built-in architectures like multilayer perceptron, multilayer long-short term networks, Hopfield networks, and many more. As Synaptic includes more API functionalities, it is more preferable over Brain.js. It indicates that Synaptic includes more use cases than Brain.js and hence it can be considered as more useful to implement the neural network and use trainers to train the system.
Limdu.js
Limdu.js is a machine-learning framework in NodeJS which is still in alpha state and is looking for contributors. It implements support for Binary classification, multi-label classification, and real-time classification. It also supports serialization through which you can train a classifier on your own system and later use it on remote servers. It includes converting a classifier into a string and uploading it to the server to later deserialize it and use it. Hence, supporting the cause for Machine Learning, this library implements many important criteria to help you in serving your purposes.
Stdlib
Stdlib is the library used for developing machine learning supportive libraries. It includes the support for building advanced statistical models and for data analysis. In essence, it includes support for natural language processing, binary classification, linear regression in the form of distributed different libraries. Also, it includes sample datasets to train and implement actions and measure the performance of the developed program. It can also be bundled with bundlers to use in web browsers.
Use of Stdlib is common among the developers and they very well know how to make use of it efficiently to ensure desired results are obtained. Therefore, it becomes important to hire node js developers who are experts at developing app like Spotify using this framework and can unleash the full potential of each library mentioned here.
KerasJS
Including support for high-level APIs enables KerasJS to take care of the abstraction levels provided by the backend. It is mainly used to train the sets to do so and is implemented later on in the application. The only disadvantage of the library is that the models created here only runs in CPU mode. This library is more recommended to use for web browser-based applications as it covers support for it majorly.
NeuroJS
This particular library is dedicated to deep learning and it also includes the concepts for the artificial neural network to support and address the requirements for machine learning development. It also includes deep-q-networks support and actor-critic models. It is also observed to be higher performing than other libraries that include similar support.
Natural
This library is developed specifically for language-based operations like tokenizing, stemming, classification, and other such operations. However, most of the algorithms here are English specific as it is in its early stage. But support for many other languages has been added from the contributors. There is another natural language processing supportive library also, named as Compromise. It provides many basic features and it is also lightweight hence can be used easily to integrate into the web browsers.
Concluding It Up
These libraries are among the primary ones used for supporting the development of machine learning using NodeJS technology. As the field of machine learning and artificial intelligence is still unexplored and the process of research in both fields continues, it becomes ideal to integrate support for them in every platform and framework.
However, being the language (JavaScript) known to web developers and also being there for a long duration of time to get known among all, NodeJS poses as a better platform to use for developing the machine learning-based applications as it is understood by plenty of developers out there and it also eliminates the need for learning new languages to implement machine learning and artificial intelligence.
