TensorFlow: TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks. It is a popular tool for building and training machine learning models.PyTorch: PyTorch is a machine learning library based on the Torch library. It is widely used for developing deep learning models and is known for its ease of use and flexibility.
Keras: Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It is designed to enable fast experimentation with deep neural networks.
H2O.ai: H2O.ai is an open-source machine learning platform that makes it easy to build and deploy machine learning models. It is known for its ease of use and scalability.
IBM Watson Studio: IBM Watson Studio is a cloud-based data science and machine learning platform that allows you to build, train and deploy machine learning models. It includes a range of tools for data preparation, model building, and deployment.
Microsoft Azure Machine Learning Studio: Microsoft Azure Machine Learning Studio is a cloud-based platform for building, deploying, and managing machine learning models. It includes a range of tools for data preparation, model building, and deployment.
Google Cloud AI Platform: Google Cloud AI Platform is a cloud-based platform for building, deploying, and managing machine learning models. It includes a range of tools for data preparation, model building, and deployment.
Amazon SageMaker: Amazon SageMaker is a cloud-based platform for building, deploying, and managing machine learning models. It includes a range of tools for data preparation, model building, and deployment.
DataRobot: DataRobot is an automated machine learning platform that allows you to build and deploy machine learning models quickly and easily. It includes a range of tools for data preparation, model building, and deployment.
RapidMiner: RapidMiner is a data science platform that allows you to build and deploy machine learning models. It includes a range of tools for data preparation, model building, and deployment.