PyTorch is still growing, while TensorFlow’s growth has stalled. Graph from StackOverflow trends . StackOverflow traffic for TensorFlow might not be declining at a rapid speed, but it’s ...

The evolution of PyTorch. Early on, academics and researchers were drawn to PyTorch because it was easier to use than TensorFlow for model development with graphics processing units (GPUs ...

Well, certainly. It’s not like TensorFlow has stood still for all that time. TensorFlow 1.x was all about building static graphs in a very un-Python manner, but with the TensorFlow 2.x line, you ...

PyTorch has a rapidly growing community, especially in the research sector, and is gaining on TensorFlow. Debugging PyTorch allows for straightforward debugging using standard Python tools.

While Tensorflow was not listed among programming languages, O’Reilly noted the machine learning library is bound to Python as well as Java, C++ and Javascript. Source: O’Reilly Media Also benefitting ...

You should use PyTorch if you are a machine learning researcher or AI engineer who values flexibility and a Python-friendly interface. PyTorch is ideal for tasks that require dynamic computation ...

Companies desperately need AI talent across all industries, not just technology firms that beginners mistakenly think ...

PyTorch 1.0 combines the best of Caffe2 and ONNX. It's one of the first frameworks to have native support for ONNX models. TensorFlow, an open source project backed by Google, is used in research ...

Like Google's TensorFlow, PyTorch is a library for the Python programming language — a favorite for machine learning and AI — that integrates with important Python add-ons like NumPy and data ...

First is PyTorch, with its tremendous following and mindshare. If you look at the metrics alone it might be easy to miss, but PyTorch is quite possibly the most used and talked about deep learning ...