It uses a domain-specific compiler for linear algebra (XLA) to JIT-compile subgraphs of TensorFlow computations (data flow graphs). A version of XLA that supports Google Tensor Processing Units ...

According to its site, TensorFlow is an open source software library for numerical computation using data flow graphs. For a layman, TensorFlow can be considered as a system that takes ...

TensorFlow is an open source software library developed by Google for numerical computation with data flow graphs. This TensorFlow guide covers why the library matters, how to use it and more.

The term "flow" refers to this movement of data through the various stages of model training or inference. Graphs: One of the reasons for TensorFlow’s popularity is its graph-based architecture.

TensorFlow is an open source software library developed by Google for numerical computation with data flow graphs. It offers tremendous opportunities for developers building machine learning into ...

At a technical level, TensorFlow facilitates numerical computation by using data flow graphs. According to Google (now a subsidiary of Alphabet (NASDAQ: GOOG), data flow graphs describe mathematical ...

Machine learning frameworks like Google’s TensorFlow ease the process of acquiring data, training models ... into TensorFlow apps. Each graph operation can be evaluated and modified separately ...

Here are the nitty-gritty details: the TensorFlow system uses data flow graphs. In this system, data with multiple dimensions (values) are passed along from mathematical computation to ...

Bonus: TensorFlow is for more than just machine learning. It may be useful wherever researchers are trying to make sense of very complex data--everything from protein folding to crunching ...

According to its site, TensorFlow is an open source software library for numerical computation using data flow graphs. For a layman, TensorFlow can be considered as a system that takes ...