TensorFlow, created by Google, is an open source library for fast numerical computing; it was designed for use in research, development, and production systems.
TensorFlow is an end-to-end platform that makes it much easier to build and deploy machines and deep learning models. It has a flexible, comprehensive ecosystem of tools, libraries, and vast community resources to aid researchers. Let’s have a look at what TensorFlow has to offer.
TensorFlow provides users with multiple levels of abstractions to choose from. Building and training machine learning models using the Keras API eases the process of getting started with TensorFlow. For very large ML problems, the Distribution Strategy API is available for distributed training on different hardware configurations; this can be done without having to modify the model in any way.
TensorFlow allows easy training and deployment of the models regardless of the language or platform. TensorFlow offers various extensions to suit a variety of platforms:
Highly complex models can be trained and deployed without any compromise on speed or performance. TensorFlow gives you flexibility and control by providing several feature APIs that include the Keras functional API and the Model Subclassing API. It also enables configurations of powerful add-on libraries for the creation and handling of highly complex topologies.