No longer the upstart nipping at TensorFlow’s heels, PyTorch is a major force in the deep learning world today, perhaps primarily for research, but also in production applications more and more.

Both PyTorch and TensorFlow support deep learning and transfer learning. Transfer learning, which is sometimes called custom machine learning, starts with a pre-trained neural network model and ...

Reinforcement Learning and Deep Learning. TensorFlow’s capabilities in reinforcement learning are worth noting, particularly its ability to facilitate complex, state-of-the-art algorithms in ...

TensorFlow is, as of now, the most widespread deep learning framework. It gets almost twice as many questions on StackOverflow every month as PyTorch does. TNW Conference 2025 - That's a wrap!

While PyTorch is an excellent deep learning framework, there are other options worth exploring. TensorFlow , developed by ...

Developers can submit ML training jobs created in TensorFlow, Keras, PyTorch, Scikit-learn, and XGBoost. Google now offers in-built algorithms based on linear classifier, wide and deep and XGBoost ...

By optimizing TensorFlow with the Intel MKL-DNN primitives means that deep learning applications built using this widely available framework can now run much faster on the latest Intel processors. The ...

PyTorch is an open-source machine learning library developed by Facebook’s AI Research lab (FAIR). It’s known for its flexibility, ease of use, and as a powerful tool for deep learning ...

While PyTorch is an excellent deep learning framework, there are other options worth exploring. TensorFlow , developed by Google, is a strong alternative, particularly for large-scale AI ...