Best JavaScript machine learning libraries in 2021

JavaScript, traditionally known for frontend development, has evolved into a versatile programming language with extensive capabilities in machine learning through various libraries. Key JavaScript libraries for machine learning include Synaptic, Brain.js, TensorFlow.js, Mind, ConvNetJS, ML5.js, Neuro.js, and Keras.js, each offering unique features and advantages. Synaptic, for instance, is notable for its architecture-free algorithm and ability to build diverse neural network architectures, while Brain.js leverages GPU for fast computation and offers ease of use with its neural network implementations. TensorFlow.js is a comprehensive library by Google that supports both training and inference in the browser, making it a staple for deep learning projects. Mind offers flexibility with matrix implementations and easy plugin integration, whereas ConvNetJS focuses on deep learning models within the browser environment. ML5.js provides a user-friendly interface for accessing pre-trained models, and Neuro.js excels in reinforcement learning and real-time classification. Finally, Keras.js, backed by major organizations, facilitates executing models in the browser with WebGL support. These libraries demonstrate JavaScript's growing prominence in machine learning and data science, offering developers an array of tools to create robust and scalable solutions.