This article we will walk you through and compare the code usability and ease to use of TensorFlow and PyTorch on the most widely used MNIST dataset to classify handwritten digits. Two of the most ...

A subcategory of machine learning, deep learning uses multi-layered neural networks to automate historically difficult machine tasks—such as image recognition, natural language processing (NLP), and ...

The two top open-source libraries for AI are TensorFlow, with more than 16000 stars, and PyTorch, with more than 21000 stars in GitHub. They have relational and non-relational data storage ...

In the dynamic world of machine learning, two heavyweight frameworks often dominate the conversation: PyTorch and TensorFlow. These frameworks are more than just a means to create sophisticated ...

At this period, TensorFlow and PyTorch are two of the most famous frameworks within deep learning. Each has its merits and demerits and serves different purposes for the AI and machine learning ...

Not every regression or classification problem needs to be solved with deep learning. For that matter, not every regression or classification problem needs to be solved with machine learning. After ...

Is PyTorch better than TensorFlow for general use cases? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.

There is a vast array of deep learning frameworks, and many of them are viable tools, but the duopoly of TensorFlow and PyTorch is evident. TensorFlow and PyTorch are the most popular frameworks for ...