Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment The importance of machine learning and deep learning is no longer ...

If you actually need a deep learning model, PyTorch and TensorFlow are both good choices ...

Most deep learning books are based on one of several popular Python libraries such as TensorFlow, PyTorch, or Keras. In contrast, Grokking Deep Learning teaches you deep learning by building ...

Python is a popular programming language for deep learning due to its simplicity, flexibility, and the availability of a vast array of open-source libraries.

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

TensorFlow 2.0 improves performance on Volta and Turing GPUs, increases deployment options, boasts tighter integration with Keras, and makes the platform easier for Python frequents.

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.

Google announced yesterday that its Deep Learning algorithm, TensorFlow, has been open-sourced. According to Google, this is the second generation machine learning algorithm, with the first one ...

Xiaoyi Lu from Ohio State University gave this talk at the 2019 OpenFabrics Workshop in Austin. "Google's TensorFlow is one of the most popular Deep Learning (DL) frameworks. We propose a unified way ...