How is TensorFlow used in machine learning?

TensorFlow enables this process of building, training, and deploying models with the aid of machine learning across a wide range of applications, from image recognition and natural language processing to recommendation systems. It provides a complete ecosystem of tools for Keras-high-level model building, TensorFlow Extended (TFX) for production workflows, and TensorFlow Lite for mobile and embedded deployments. TensorFlow supports neural networks and deep learning to design complex architectures such as convolutional and recurrent neural networks. Flexible from cloud to edge devices, TensorFlow supports a huge range of platforms and is interoperable with other languages such as Python and JavaScript, making it suitable for end-to-end machine learning pipelines.