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Machine Learning (13 results) showing 1 - 10



The AWS Deep Learning Containers for MXNet include containers for training and inference for CPU and GPU, optimized for performance and scale on AWS. These Docker images have been tested with SageMaker, EC2, ECS, and EKS and provide stable versions of NVIDIA CUDA, cuDNN, Intel MKL, and other...


A fully pre-configured Deep Learning Container with TensorFlow 2.0 and open-source libraries for machine learning, including Jupyter Lab & Notebook, Keras, Theano, PyTorch, OpenCV, H2O, CNTK, NVIDIA CUDA, cuDNN, Numpy, Scipy, scikit-learn, XGBoost, etc. The container provides a seamless user...


The AWS Deep Learning Containers for PyTorch include containers for training and inference for CPU and GPU, optimized for performance and scale on AWS. These Docker images have been tested with SageMaker, EC2, ECS, and EKS and provide stable versions of NVIDIA CUDA, cuDNN, Intel MKL, Horovod and...

  • Version 180906t1100k222p363j100
  • Sold by Jetware

A pre-configured and fully integrated minimal runtime environment with TensorFlow, an open source software library for machine learning, Keras, an open source neural network library, Jupyter Notebook, a browser-based interactive notebook for programming, mathematics, and data science, and the...


PyTorch is a deep learning platform that accelerates the transition from research prototyping to production deployment. Bitnami image includes Torchvision for specific computer vision support. Why Use Bitnami Container Solutions? Bitnami certifies that our containers are secure, up-to-date,...


The AWS Deep Learning Containers for TensorFlow include containers for training and inference for CPU and GPU, optimized for performance and scale on AWS. These Docker images have been tested with SageMaker, EC2, ECS, and EKS and provide stable versions of NVIDIA CUDA, cuDNN, Intel MKL, Horovod and...


TensorFlow ResNet is a client utility for use with TensorFlow Serving and ResNet models. Why Use Bitnami Container Solutions? Bitnami certifies that our containers are secure, up-to-date, and packaged using industry best practices. Bitnami container solutions can be used with Kubeapps for...


MXNet is a flexible and efficient library for deep learning designed to work as a neural network. Bitnami image ships OpenBLAS as math library. Why Use Bitnami Container Solutions? Bitnami certifies that our containers are secure, up-to-date, and packaged using industry best practices....


Horizon is an open source end-to-end platform for applied reinforcement learning (RL) developed and used at Facebook. Horizon is built in Python and uses PyTorch for modeling and training and Caffe2 for model serving. The platform contains workflows to train popular deep RL algorithms and includes...

  • Version 18.11
  • Sold by NVIDIA

MXNet is a deep learning framework that allows you to mix the flavors of symbolic programming and imperative programming to maximize efficiency and productivity.