TensorFlow.js, Google’s open-source library, is helping to make machine learning possible in the browser. Machine Learning and Data Analysis through JavaScriptīuilding and training machine-learning models using a web-scripting language might seem ambitious, but in 2020, it is entirely feasible. Companies like eBay, NASA, Uber, Walmart, Netflix, and LinkedIn have all spoken openly about moving towards or making heavy use of Node.js, which confirms the opinion mentioned above. If one is exceptionally proficient in JavaScript, which already accounts for many components of the web, using it on the backend allows them to make changes more quickly. The primary reason is quite simple – application development in JavaScript on the frontend and backend are generally considered to be more cost-effective to build and easier to maintain. To be clear – it will not supplant all core backend technologies as many large firm backends are composed of multiple technologies and not just a single one. The use of Node.js is poised to continue to grow over the next several years. On the other side, most startups use JavaScript to develop backend services with the help of the Node.js framework.
Another key feature is that all the top web browsers, including Google Chrome, Internet Explorer, Firefox, Edge, Safari, and Opera, all support JavaScript. Moreover, open-source JavaScript has played a significant role in digital transformation by creating interactive web pages using frontend development frameworks. According to the latest survey, JavaScript remains the most popular programming language for more than half of all developers. The main reason is that it’s a light-weighted programming language that can easily be integrated with other frameworks/languages. “Any application that can be written in JavaScript, will eventually be written in JavaScript.” – Atwood’s LawĪtely, JavaScript is becoming one of the most powerful languages because of its performance and universal acceptance.
0 kommentar(er)
