Web Based AI Application

WHAT'S THE BEST STACK FOR BUILDING WEB BASED AI APPLICATION
There are several technology stacks that can be used for building web-based AI applications, and the best stack depends on several factors such as the specific needs of the application, the size and complexity of the data, the target audience, and the expertise of the development team. That being said, here are some popular technology stacks that are commonly used for building web-based AI applications: Python-based stack: Python is a popular language for building AI applications, and it has many libraries and frameworks that can be used for web development, such as Flask, Django, and FastAPI. These frameworks make it easy to build RESTful APIs and web applications that can interact with machine learning models. JavaScript-based stack: JavaScript is a popular language for building web applications, and it also has several libraries and frameworks that can be used for building AI applications. Some popular frameworks include TensorFlow.js, Brain.js, and Synaptic.js. These frameworks allow for the development of browser-based AI applications and real-time machine learning. MEAN stack: The MEAN stack is a popular full-stack development framework that uses MongoDB, Express, AngularJS, and Node.js. This stack is particularly well-suited for building scalable and high-performance web-based AI applications. LAMP stack: The LAMP stack is another popular full-stack development framework that uses Linux, Apache, MySQL, and PHP. This stack is particularly well-suited for building web applications with complex data processing and analysis requirements. Ultimately, the best stack for building web-based AI applications will depend on the specific requirements and constraints of your project, as well as the preferences and expertise of your development team.