Showing 2 open source projects for "numpy-mkl"

View related business solutions
  • Go From Idea to Deployed AI App Fast Icon
    Go From Idea to Deployed AI App Fast

    One platform to build, fine-tune, and deploy. No MLOps team required.

    Access Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
    Try Free
  • Cut Your Data Warehouse Bill by 54% Icon
    Cut Your Data Warehouse Bill by 54%

    Migrate from Snowflake, Redshift, or Databricks with free tools. No SQL rewrites.

    BigQuery delivers 54% lower TCO with serverless scale and flexible pricing. Free migration tools handle the SQL translation automatically.
    Try Free
  • 1
    AWS Deep Learning Containers

    AWS Deep Learning Containers

    A set of Docker images for training and serving models in TensorFlow

    AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. ...
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2
    SageMaker MXNet Inference Toolkit

    SageMaker MXNet Inference Toolkit

    Toolkit for allowing inference and serving with MXNet in SageMaker

    ...AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB