TensorFlow and PyTorch are two of the most popular deep learning frameworks for the Python programming language. This aricle provides a detailed comparison of TensorFlow vs PyTorch. Do you know about this comparison yet? Read this article to expand your knowledge right away.
Deep learning is a common technique of solving real-world problems using human-like computers.
Deep learning tasks involve the creation of special brain-like architectures known as artificial neural networks.
To help develop such architectures, various Python frameworks for performing deep learning tasks have been developed, making it easier to build and train diversified artificial neural networks.
The two most popular frameworks for performing deep learning tasks are TensorFlow and PyTorch.
If you've ever done a deep learning task, you must have heard about the above terms.
Maybe, you've been trying to figure out which one to choose, or you're just starting your deep learning journey and you're asking yourself this question...
"Which one is better?"
This forms the subject of discussion in this tutorial.
I'll be resolving all your doubts about these two popular frameworks and help you choose the one that suits your needs.
You can skip to a specific section of this tutorial using the table of contents below:
With the Deep Learning scene being dominated by three main frameworks, it is very easy to get confused on which one to use? In this video on Keras vs Tensorflow vs Pytorch, we will clear all your doubts on which framework is better and which framework should be used by beginners, intermediates and professionals.
We will go over what is the difference between pytorch, tensorflow and keras in this video. Pytorch and Tensorflow are two most popular deep learning frameworks. Pytorch is by facebook and Tensorflow is by Google. Keras is not a full fledge deep learning framework, it is just a wrapper around Tensorflow that provides some convenient APIs.
Deep learning is a subset of Artificial Intelligence (AI), a field growing popularly over the last several decades. Deep learning and machine learning are part of the artificial intelligence family, though deep learning is also a subset of machine learning. Keras vs Tensorflow vs Pytorch
We will go through some of the popular deep learning frameworks like Tensorflow, MxNet, DL4j, PyTorch and CNTK so you can choose which one is best for your project. Deep Learning is a branch of Machine Learning. Though machine learning has various algorithms, the most powerful are neural networks. To build these neural networks, we use different frameworks like Tensorflow, CNTK, and MxNet.
JAX is a Python library designed for high-performance numerical computing.