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    ML Workbench for PyTorch

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    Sold by: netCUBED 
    Free Trial
    Ubuntu 20.04 with Jupyter, JupyterLab and preconfigured conda environments for PyTorch 1.11 including the latest matching versions of CUDA and cuDNN for GPU-accelerated computing.
    Listing Thumbnail

    ML Workbench for PyTorch

     Info
    Sold by: netCUBED 

    Overview

    Ubuntu 20.04 with Jupyter, JupyterLab, TensorBoard, RStudio Server and preconfigured conda environments for PyTorch 1.11 including the latest matching versions of CUDA 11.3, cuDNN 8 and NCCL for GPU-accelerated computing. There is no need for an SSH session to launch a notebook. All services, including the Ubuntu MATE desktop, can be accessed through the browser. Check out the video to see how to start training your first model on a GPU in less than 5 minutes.

    https://www.youtube.com/watch?v=NmdDMh1foSE 

    Additionally, this environment provides a full-featured Ubuntu MATE desktop environment and direct console access through the browser with the latest versions of Google Chrome, Visual Studio Code and Docker (including the NVIDIA Container Runtime).

    The Machine Learning Workbench puts a focus on security. All communication to the instance is encrypted, launching and accessing the Jupyter Notebook requires username and password authentication.

    Highlights

    • ZERO CONFIGURATION: Immediately get started with developing and training your model
    • SECURE: Encryption in transit by default and strong user authentication
    • NO SSH NECESSARY: All features, including tensorboard, jupyter notebook and the graphical desktop environment, can be accessed through the browser

    Details

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    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    Ubuntu 20.04

    Typical total price

    This estimate is based on use of the seller's recommended configuration (t3.medium) in the US East (N. Virginia) Region. View pricing details

    $0.082/hour

    Pricing

    Free trial

    Try this product at no cost for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.

    ML Workbench for PyTorch

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covering your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (215)

     Info
    • ...
    Instance type
    Product cost/hour
    EC2 cost/hour
    Total/hour
    t2.small
    $0.03
    $0.023
    $0.053
    t2.medium
    $0.04
    $0.046
    $0.086
    t2.large
    $0.05
    $0.093
    $0.143
    t2.xlarge
    $0.06
    $0.186
    $0.246
    t2.2xlarge
    $0.07
    $0.371
    $0.441
    t3.small
    $0.03
    $0.021
    $0.051
    t3.medium
    Recommended
    $0.04
    $0.042
    $0.082
    t3.large
    $0.05
    $0.083
    $0.133
    t3.xlarge
    $0.06
    $0.166
    $0.226
    t3.2xlarge
    $0.07
    $0.333
    $0.403

    Additional AWS infrastructure costs

    Type
    Cost
    EBS General Purpose SSD (gp3) volumes
    $0.08/per GB/month of provisioned storage

    Vendor refund policy

    We do not currently support refunds, but you can cancel at any time.

    Legal

    Vendor terms and conditions

    Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

    Content disclaimer

    Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.

    Usage information

     Info

    Delivery details

    64-bit (x86) Amazon Machine Image (AMI)

    Amazon Machine Image (AMI)

    An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

    Version release notes

    Upgrade Ubuntu 20.04 to include latest security updates, updated PyTorch to 1.11 and CUDA to 11.3.

    Additional details

    Usage instructions

    Launch the image on any of the available instance types. Consider changing the size of the root EBS volume. Make sure that the attached security group allows traffic on port 80 and 443 if you plan to access the server via the browser interface, and port 3389 if you plan to use the Remote Desktop Protocol. Allow a couple of minutes for the instance to boot.

    The web interface can be accessed through your browser on the public IP (or private IP for enterprise VPCs) of the EC2 instance (e.g. https://18.245.21.43  where 18.245.21.43 is the public IP address of the instance).

    Most browsers will display a certificate warning. This warning is letting you know that the certificate was self-signed instead of signed by a trusted Certificate Authority. You can safely ignore the warning as it doesn't impact the security of the connection by clicking on "Continue to this webpage" (Internet Explorer) or "Advanced" and then "Proceed to website" (Chrome).

    The default user is ubuntu and the default password is the instance ID.

    Alternatively, you can reach your desktop environment through a Remote Desktop Client (such as the Microsoft Remote Desktop Application, preinstalled on Windows and available on the Apple App Store for MacOS). The hostname is simply the public IP (or private IP for enterprise VPCs). Make sure you enter the username and password before you connect. On Windows, click "Show Options" and fill in the username and password.

    Resources

    Support

    Vendor support

    For paid support, email sales@netcubed.de  for further information. Free support is provided via support@netcubed.de . For free support, we do not provide a guaranteed response time, however we do our best to respond to questions within 24 hours Monday through Friday.

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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    Customer reviews

    Ratings and reviews

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    1 AWS reviews
    pr

    Works well until you get an authentication error

    Reviewed on Mar 30, 2021
    Purchase verified by AWS

    The password is supposed to be the instance ID. THat will work for the first few times you use it then it stops working.

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