Let’s learn about open-source AI frameworks in this tutorial. An AI framework is a software framework that allows developers and researchers to build and deploy Artificial Intelligence(AI) applications and Machine Learning(ML) models.
These frameworks provide developers with a wide range of features such as machine learning algorithms, deep learning, neural network architectures, optimization techniques, and data-processing capabilities.
Open Source AI Frameworks
There are several open-source AI frameworks currently available in the IT market. Some of them are as follows:
TensorFlow is an open-source E2E(end-to-end) platform developed by Google, Inc. TensorFlow is a powerful framework for building and training deep learning models. It makes it easy to build and deploy ML(Machine Learning) models.
TensorFlow provides a wide range of tools and APIs for creating neural networks and supports a variety of programming languages including Python, C++, and Java.
More information: https://www.tensorflow.org/
PyTorch is a popular open-source deep-learning framework developed by Facebook. PyTorch is flexible and easy to use. It allows users to create and train neural networks using dynamic computational graphs and supports a range of deployment options including mobile devices and the web.
More Information: https://pytorch.org/
Cafee is a popular deep-learning framework developed by the Berkeley Vision and Learning Center (BVLC). It is optimized for speed and efficiency. It provides a simple and expressive architecture for defining and training neural networks and supports a range of network architectures including convolutional and recurrent neural networks.
More Information: https://caffe.berkeleyvision.org/