Sold by: pCloudHosting LLC
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
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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
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.
Dimension | Cost/hour |
|---|---|
m4.large Recommended | $0.10 |
t2.micro | $0.001 |
t3.micro | $0.10 |
t3.nano | $0.10 |
t3.medium | $0.10 |
t2.2xlarge | $0.10 |
t2.medium | $0.10 |
t2.large | $0.10 |
t3.large | $0.10 |
r3.large | $0.10 |
Dimensions summary
You pay by the hour for the EC2 instance type you run. All 21 dimensions bill the same AutoML software with maintenance support; they differ only by the underlying compute size. The t2 and t3 families cover general-purpose sizes from nano through 2xlarge. The m3, m4, and m5 large sizes offer balanced compute and memory. The r3, r4, and r5 large sizes target memory-heavy workloads. The c3, c4, and c5 large sizes target compute-heavy workloads. Your hourly rate scales with the capacity and family you select. No upfront commitment applies.
Top-of-mind questions for buyers
Each rate maps to one running EC2 instance of the chosen type, preloaded with the AutoML software on Ubuntu 26.04 plus maintenance support. The instance size sets your compute cores and memory. You pay for each hour the instance runs, per instance you launch.
The software fee meters running time only. A fully stopped instance stops accruing the hourly software charge. Attached AWS storage and other AWS infrastructure fees may still apply while the instance is stopped. Restarting the instance resumes the hourly software charge automatically.
The listing bundles maintenance support with the software. The vendor performs scheduled maintenance to update servers and software, and may run emergency maintenance without notice, which can briefly suspend access. Support and updates come with your active use during the applicable term.
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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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