Аплайнсы
The pre-configured and ready-to-use runtime environment for the MIT 6.S094 course: Deep Learning for Self-Driving Cars, 2017. It includes Python 2.7, TensorFlow 0.12.1 and OpenCV 3.3.0. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
The pre-configured and ready-to-use runtime environment for the MIT 6.S094 course: Deep Learning for Self-Driving Cars, 2017. It includes Python 2.7, TensorFlow 0.12.1 and OpenCV 3.3.0. The software stack is optimized for running on CPU.
A pre-configured and fully integrated software stack with TensorFlow, an open source software library for machine learning, Python 2.7, and Jupiter Notebook, a browser-based interactive notebook for programming, mathematics, and data science. The stack is designed for research and development tasks and optimized for running on NVidia GPU.
A pre-configured and fully integrated software stack with TensorFlow, an open source software library for machine learning, Python 2.7, and Jupiter Notebook, a browser-based interactive notebook for programming, mathematics, and data science. The stack is designed for research and development tasks and optimized for running on CPU.
A pre-configured and fully integrated software stack with Theano, a numerical computation library for Python, and Python 2.7. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on NVidia GPU.
A pre-configured and fully integrated software stack with Theano, a numerical computation library for Python, and Python 2.7. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on CPU.
A pre-configured and fully integrated software stack with TensorFlow, an open source software library for machine learning, and Python 2.7. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on NVidia GPU.