TensorFlow is an open-source machine learning framework developed by Google Brain Team and released under the Apache 2.0 license. It is an end-to-end platform for developing and deploying deep learning models. TensorFlow has become the most popular AI framework for building and deploying deep learning models for both research and production. It provides a comprehensive library of tools, libraries, and resources for designing, building, and training deep learning models (Kumar, 2020).
TensorFlow can be used for a variety of tasks such as image classification, object detection, speech recognition, natural language processing, and video analysis. It also provides tools for training deep learning models with an easy-to-understand API. The main components of TensorFlow are the TensorFlow Core, which provides a low-level API for constructing and executing computations, and TensorFlow Estimators, which provide high-level APIs for building and training models.
TensorFlow has been widely adopted by the industry for its wide range of use cases and its powerful programming model. It has been used by tech giants such as Google, Facebook, Microsoft, and Apple for their deep-learning projects. It is also widely used by researchers in academic institutions and startups as well (Bhandari & Pandey, 2019).
TensorFlow has also gained popularity due to its focus on simplicity, performance, and scalability. It is designed to make scaling up models easy and efficient. It also supports automatic differentiation for training, as well as GPU and TPU acceleration for training large models. This makes it an ideal choice for production-level applications.
In conclusion, TensorFlow is the most popular deep learning framework used by researchers and industry professionals. It offers a wide range of tools and resources for developing and deploying deep learning models. It is also highly scalable, allowing for efficient training of large models.