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    AutoML on Ubuntu 26.04 with maintenance support by pCloudHosting

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    Deployed on AWS
    AWS Free Tier
    This product has charges associated with it for seller support. MLJAR AutoML is an open-source automated machine learning framework for Python that simplifies the process of building, training, and evaluating machine learning models. It automatically performs feature engineering, model selection, and hyperparameter tuning, enabling users to create high-quality predictive models with minimal manual effort.

    Overview

    MLJAR AutoML is a powerful and user-friendly automated machine learning (AutoML) framework designed for Python. It enables developers, data scientists, and analysts to quickly build accurate machine learning models without requiring extensive expertise in model selection or parameter optimization.

    The framework automates essential stages of the machine learning workflow, including data preprocessing, feature engineering, algorithm selection, hyperparameter tuning, and model evaluation. MLJAR AutoML supports popular machine learning libraries and can generate explainable models along with detailed reports, making it suitable for both beginners and experienced practitioners.

    Key Features of MLJAR AutoML:

    • Automated data preprocessing and feature engineering.
    • Automatic model selection and hyperparameter optimization.
    • Support for multiple algorithms, including XGBoost, LightGBM, CatBoost, and Random Forest.
    • Generation of interpretable models and detailed reports.
    • Easy integration with Python applications and data science workflows.
    • Suitable for classification, regression, and ensemble learning tasks.

    MLJAR AutoML is widely used for rapid prototyping, predictive analytics, and machine learning projects where reducing development time and improving model performance are important. Its automation capabilities help users focus on solving business problems rather than manually tuning machine learning algorithms.

    Highlights

    • Automates model selection, feature engineering, and hyperparameter tuning.
    • Supports multiple machine learning algorithms with explainable model reports.

    Details

    Delivery method

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

    Latest version

    Operating system
    Ubuntu 26.04

    Deployed on AWS
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    Pricing

    AutoML on Ubuntu 26.04 with maintenance support by pCloudHosting

     Info
    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.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.
    If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier  for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier  for more details.

    Usage costs (21)

     Info
    Dimension
    Cost/hour
    m4.large
    Recommended
    $0.03
    t3.micro
    $0.03
    t2.micro
    $0.01
    t2.small
    $0.03
    m5.large
    $0.03
    m3.large
    $0.03
    t2.xlarge
    $0.03
    r5.large
    $0.03
    c5.large
    $0.03
    c4.large
    $0.03

    Vendor refund policy

    No Refund

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    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

    Packaged with latest updates as of June/2026

    Additional details

    Usage instructions

    Connect your instance via SSH, the username is ubuntu. More info on SSH: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html  - Run the following commands: #source /opt/mljar-env/bin/activate #python -c "import supervised; print(supervised.version)"

    Support

    Vendor support

    Feel free to reach out anytime. Our support team is available 24x7 for assistance. Email: anant.shahi@pcloudhostings.com  Website:

    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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