Overview
JavaScript plays an important role in website development. Developers use JavaScript for combining machine learning features with the browser-based application or web page.
These JavaScript frameworks help in improving business growth through AI and Machine learning.
Javascript is throughout, from work to projects, enhanced by languages such as ReasonML and Typescript.
Javascript Machine Learning has witnessed a leap of growth and has been evolving throughout the year of 2019 and up until now.
The unbelievable growth in new technologies like machine learning has helped web developers create new AI applications in easier ways than ever. Many JavaScript-based frameworks are also being implemented in AI.
Importance of Web Applications and Machine Learning
Web applications enable organizations to serve the requirements of many clients, carried across over different land areas, without needing any geographic business process.
Web applications worked as information gathering platforms. Machine learning is developing quickly and can be incorporated into Web applications in different ways.
Today, machine learning is one of the most popular trends in software development. Many analysts even understand that machine learning will eventually transform the development process of different software including web applications.
7 Best JavaScript libraries in Machine Learning:
Mentioned below are some of the best JavaScript frameworks for machine learning that are going to rule.
1) ConvNetJS
ConvNetJS is a JavaScript library that allows a user to create and solve JavaScript neural networks while maintaining neural network modules.
It specifies and trains convolutional networks and is one of the most excellent tools to execute deep learning models in Node.js. Furthermore, it also helps in JavaScript data debugging and encryption.
2) Synaptic
Synaptic is a JavaScript neural network library for node.js or in the web browser. It is architecture-free hence one can easily practice and design any first-order or even second-order neural network architecture.
This library includes pre-manufactured structures that allow you to quickly test and look at different calculations like multilayer perceptrons, long short-term memory, etc.
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3) Brain.js
Brain.js is a GPU-accelerated library written in JavaScript for neural networks. This library is easy to use and performs computations using GPU.
It provides various neural network implementations and different neural nets can be trained to do several things. It runs with an assortment of networks for various purposes like repetitive neural systems and feed-forward neural systems.
4) TensorFlow.js
TensorFlow.js is an open-source hardware-accelerated library that is written in JavaScript for the advancement of deep learning and machine learning models.
It provides simple APIs to load and parse data over the web in various formats, and to provide that data for use in machine learning models.
This free platform includes numerous libraries and tools for the developer.
5) Machinelearn.js
Machinelearn.js is a machine learning library for the web which is suitable for many developers that are not familiar with machine learning.
It solves various machine learning challenges and guides users on how the machine learning algorithm works. Its main characteristic is its simplicity to solve complex problems by running a machine learning algorithm.
6) Deeplearn.js
Deeplearnjs is a hardware-accelerated open-source JavaScript library for machine intelligence. It allows the developers to quickly train & build different types of neural network models within the Chrome browser.
It is a development environment for deep learning created for simplicity, and reproducibility of experiments and can run pre-trained models in inference mode.
7) Math.js
Math.js is an extended math library for Node.js and JavaScript. It comes with a huge set of built-in functions and constants.
This library offers integrated solutions to work with different data types like fractions, complex numbers, matrices, and units. It gives all the basic utilities that are required to solve machine learning issues.
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Conclusion
Machine learning is considered one of the growing technologies and JavaScript helps to implement machine learning in web app development.
Both JavaScript and machine learning have gained much attention and demand during the most recent years.
We have discussed the top 7 JavaScript machine frameworks which are worth considering for your web development.
Therefore, these JavaScript machine learning libraries will be useful if you’re looking for a substitute to python frameworks for machine learning and development.
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