Streamline your machine learning tasks with these open-source libraries and tools for deep learning and general-purpose use:

• amazon-dsstne - A scalable deep learning framework for building recommendation engines and other large-scale machine learning applications.
• caffe - A fast and efficient deep learning framework that can be used for image classification, segmentation, and other tasks.
• chainer - A flexible and powerful deep learning framework that enables rapid prototyping and experimentation.
• cntk - A deep learning toolkit that provides fast, scalable training and inference across multiple GPUs and servers.
• deepdetect - A machine learning server that makes it easy to integrate state-of-the-art deep learning models into your applications.
• deeplearning4j - A distributed deep learning library that runs on the JVM and is designed for scalability and performance.
• fastai - A deep learning library that provides high-level abstractions for building and training models, along with tutorials and pre-trained models.
• gym - A toolkit for developing and comparing reinforcement learning algorithms, featuring a wide range of environments and benchmarks.
• keras - A user-friendly deep learning library that provides a simple, intuitive API for building and training models.
• mxnet - A flexible and efficient deep learning library that supports a variety of programming languages and hardware platforms.
• neon - A deep learning framework that is optimized for performance on Intel processors and provides a high-level API for building and training models.
• neupy - A Python library for building and training artificial neural networks and other deep learning models.
• neural-enhance - A deep learning tool that can enhance the resolution and quality of images using a variety of techniques.
• Paddle - A flexible and easy-to-use deep learning framework that supports a wide range of applications, from image classification to natural language processing.
• singa - A distributed deep learning system that provides fast and efficient training on a variety of hardware platforms.
• sonnet - A TensorFlow-based deep learning library that provides a modular and composable approach to building and training models.
• swflow - A simplified interface for TensorFlow that makes it easy to build and train deep learning models for a variety of tasks.
• tensorflow - An open-source deep learning library that provides a flexible and scalable platform for building and training models.
• tensorpack - A deep learning library that provides a set of high-level abstractions for building and training models with TensorFlow.