Machine Learning is revolutionizing the world. Let's explore 10 open source frameworks that make it accessible to everyone.
Developed by Google Brain, TensorFlow is a powerful library for numerical computation and large-scale machine learning.
Keras is a user-friendly neural network library written in Python. It's built on top of TensorFlow.
Created by Facebook's AI Research lab, PyTorch is a deep learning framework that provides maximum flexibility and speed.
Scikit-Learn is a Python library for machine learning and data mining, providing simple and efficient tools for data analysis.
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.
Caffe2 is an efficient and scalable deep learning framework developed by Facebook AI Research for model training and deployment.
MXNet is a deep learning framework that allows you to define, train, and deploy deep neural networks on a wide array of devices.
CNTK describes neural networks as a series of computational steps via a directed graph.
PaddlePaddle offers a rich set of features for deep learning with good scalability and supports a wide range of neural network architectures.
Chainer is a Python-based deep learning framework for neural networks that is designed by the run strategy.
These open-source frameworks are powering the future of machine learning. Start exploring them today!