TensorFlow is Google's open-source mainstream machine learning framework, primarily used to build, train, and deploy deep learning models, supporting end-to-end AI development from research to production.
It's mainly divided into TensorFlow 1.x and 2.x series. It is recommended for beginners and new projects to use TensorFlow 2.x (e.g., v2.16.1) because it enables eager execution by default, and its API is simpler and easier to use.
It supports CPU/GPU/TPU hardware, runs in browsers/Node.js via TensorFlow.js, deploys on mobile and IoT devices with TensorFlow Lite, and also supports cloud and on-premises servers.
A foundation in Python programming and basic machine learning concepts is recommended. Start with the official installation guide and beginner tutorials, and practice using Google Colab's free GPU environments.
TensorFlow Lite is optimized for mobile and embedded devices, enabling lightweight models; TensorFlow.js is for running machine learning models directly in JavaScript environments in the browser or Node.js.
TensorFlow is completely open source and free. Google offers an official TensorFlow Developer Certification program, through which you can earn a professional credential via courses and exams.
FlutterFlow is a visual low-code development platform designed to help you quickly build and deploy high-quality cross-platform applications using a drag-and-drop interface, spanning mobile, web, and desktop. It includes AI-assisted development, real-time data integration, and team collaboration features, making it ideal for moving from prototyping to production-ready applications.
Silicon Flow AI provides a one-stop cloud service for generative AI, integrating 50+ mainstream open-source large models, with a self-developed inference engine that significantly accelerates and reduces costs, helping developers and enterprises quickly build AI applications.
