Which of the following is a major application of TensorFlow?

TensorFlow is a powerful open-source machine learning framework developed by Google that is widely utilized for various applications in artificial intelligence and deep learning. One of its major applications is in image and speech recognition.

In the realm of image recognition, TensorFlow enables the development of convolutional neural networks (CNNs), which are particularly effective in identifying and classifying images. This application is crucial in numerous sectors, including healthcare for analyzing medical images, automotive for enhancing autonomous vehicle systems, and more.

Similarly, for speech recognition, TensorFlow supports recurrent neural networks (RNNs) and other architectures that help process and understand spoken language. This technology is embedded in virtual assistants, translation applications, and voice-activated controls, making it integral to how humans interact with machines.

While data processing, storage management, social media analytics, and financial modeling have their respective frameworks and tools, they do not leverage TensorFlow’s core capabilities in the same way that image and speech recognition do. Therefore, these applications stand out as prime use cases for TensorFlow, aligning directly with its strengths in handling large datasets for model training and execution in the domains of vision and audio processing.