At the same time, TensorFlow started to play better with standard Python infrastructure such as PyPI and pip, and with the NumPy package widely used by the scientific computing community.

The WebGL-accelerated library works with the Node.js server-side JavaScript runtime, but isn’t on par with Tensorflow’s Python API Google’s TensorFlow open source machine learning library ...

Many developers who use Python for machine learning are now switching to PyTorch. Find out why and what the future could hold for TensorFlow.

Scikit-learn, PyTorch, and TensorFlow remain core tools for structured data and deep learning tasks.New libraries like JAX, ...

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.

TensorFlow has become the most popular tool and framework for machine learning in a short span of time. It enjoys tremendous popularity among ML engineers and developers.

Netflix's data-science team has open-sourced its Metaflow Python library, a key part of the 'human-centered' machine-learning infrastructure it uses for building and deploying data-science workflows.

Moreover, developers using standard TensorFlow mechanisms shouldn’t have to change their model architectures, training procedures, or processes. It follows hot on the heels of TensorFlow 2.0 ...

Google today released TensorFlow Constrained Optimization, a library aimed at addressing issues related to measuring multiple metrics and fairness.