Analytics Insight explores the top Javascript machine learning libraries in 2021 to use

Machine learning has brought sufficient growth in new technologies to build multiple artificial intelligence models for the global tech-driven market. There are multiple programming languages in this field for the development of machine learning models. The most popular ones are Python, C++, R, and another one is Javascript. Developers leverage Javascript frameworks for these machine learning models. Different Javascript machine learning libraries are available on the Internet to bring this programming language, machine learning, and NLP together. Let's explore some of the top Javascript machine learning libraries for use in 2021.

Top Javascript machine learning libraries

TensorFlow.js

TensorFlow.js is a popular Javascript machine learning library to develop machine learning models and utilize machine learning directly in the browser as well as Node.js. There are complete tutorials on how to use this machine learning library with the programming language. It also consists of pre-trained and out-of-the-box machine learning models for common use cases across the world. Developers can use off-the-shelf Javascript models, can convert Python TensorFlow models as well as retrain pre-existing machine learning models with their own data efficiently and effectively.

ml.js

ml.js is another top Javascript machine learning library to use in 2021 that focused on making machine learning approachable for different target audiences. The machine learning library offers access to ML algorithms and models in the browser with no other external dependencies. It is an open-source and friendly high-level interface library for managing GPU-accelerated mathematical operations as well as memory management for ML algorithms. It is also popular for providing immediate access in the browser to detect human poses, text, style, image, music, and many more functionalities.

ConvNetJS

ConvNetJS is one of the top Javascript machine learning libraries for training machine learning models in the browser efficiently and effectively. Developers do not need software requirements, compilers, installations, and GPUs for training purposes with this programming language. The machine learning library enables formulation and solves neural networks in Javascript with multiple supports such as common neural network modules, classification and regression cost function, convolutional networks, and reinforcement learning modules based on deep Q learning.

Synaptic

Synaptic is a popular JavaScript machine learning library created by MIT for this programming language. This is well-known for the Javascript architecture-free machine learning library for both browsers as well as Node.js. It offers programmers to learn XOR, discrete sequence recall, image filters, image painting, self-organizing map, and many more. There is documentation available for neurons, networks, layers, trainers, and architects. This library helps to develop and train first-order and second-order neural network architecture for its pre-manufactured structure.

Brain.js

Brain.js is known for GPU-accelerated machine learning and neural network in Javascript for browsers and Node.js. Programmers can easily use this programming language without knowing in-depth details of neural networks and machine learning mechanisms. It performs computations with GPU to fall back to pure Javascript when GPU is not available. This machine learning library also helps to export and import trained machine learning models with JSON format and as a function.

Neuro.js

Neuro.js is one of the top machine learning libraries for the programming language, Javascript. It offers a machine learning framework for building artificial intelligence assistants as well as chatbots efficiently. It is a library for developing ML models in Javascript and deploying them in any browser and Node.js. It offers support to multi-label classification, online learning, and real-time classification.