Arguably one of the best deep learning frameworks that now been adopted by several giants at scale such as Airbus, Twitter, IBM and others mainly due to its highly flexible system architecture.

The most well known use case of TensorFlow has got to be Google Translate coupled with capabilities such as natural language processing, text classification/summarization, speech/image/handwriting recognition, forecasting and tagging.

TensorFlow is available on both desktop and mobile and also supports languages such as Python, C++ and R to create deep learning models along with wrapper libraries.

TensorFlow comes with 2 tools which are widely used –

  1. TensorBoard for effective data visualization of network modeling and performance
  2. TensorFlow Serving for rapid deployment of new algorithms/experiments while retaining the same server architecture and APIs. It also provides integration with other TensorFlow models which is different from the conventional practices and can be extended to serve other model and data types.

If you happen to be taking your first steps when it comes to deep learning, it is a no brainer that you should opt for TensorFlow given that is Python based, supported by Google and comes loaded with documentation and walkthroughs to guide you.