Overview
This is a repackaged open-source software product wherein additional charges apply for technical support and maintenance by Apps4Rent.
Streamline your machine learning tasks with Scikit-learn on Ubuntu 24.04 LTS, conveniently re-packaged by Apps4Rent for seamless integration on the AWS Marketplace. This powerful offering pairs the versatility of Scikit-learn, a leading machine learning library, with the stability of Ubuntu 24.04 LTS. Ensure efficient development and deployment of machine learning models with confidence, while leveraging the familiarity and security of a well-established environment.
Focus on innovation, not on complex setup procedures. Scikit-learn empowers you to build and deploy machine learning models efficiently, allowing you to tackle various tasks from classification and regression to clustering and dimensionality reduction. Build a robust foundation for your data-driven applications with the combined strengths of Scikit-learn and Ubuntu.
Experience the ease of deployment with Apps4Rent's pre-configured Scikit-learn server on the AWS Marketplace. Eliminate the complexities of manual installations and configurations, allowing you to focus on what matters most - developing and deploying machine learning models with confidence. Effortlessly scale your resources as your machine learning needs grow. The flexible nature of AWS empowers you to seamlessly adjust your Apps4Rent Scikit-learn server configuration to accommodate even the most demanding projects.
Disclaimer: The respective trademarks mentioned in the offering are owned by the respective companies. We do not provide the commercial license of any of these products. Many of the products have a free, demo, or Open-Source license as applicable. Image may take up to 5-7 minutes for the initial launch.
Highlights
- Comprehensive Machine Learning Capabilities: Scikit-learn on Ubuntu 24.04 LTS, re-packaged by Apps4Rent, offers a comprehensive suite of machine learning algorithms and tools, enabling users to tackle a wide range of tasks, including classification, regression, clustering, and dimensionality reduction. This empowers data scientists and developers to efficiently build and deploy machine learning models for various applications.
- Seamless Integration and Stability: Apps4Rent's re-packaging ensures seamless integration of Scikit-learn on Ubuntu, providing users with a stable and reliable environment for machine learning development and deployment. With Ubuntu's robustness and familiarity, combined with the versatility of Scikit-learn, users can confidently tackle machine learning projects with ease.
- Efficient Deployment and Scalability: The pre-configured Scikit-learn server on the AWS Marketplace simplifies deployment, eliminating the complexities of manual installations and configurations. As machine learning needs evolve, users can effortlessly scale resources to accommodate growing demands, thanks to the flexibility of AWS. This scalability ensures optimal performance and resource utilization, even for the most demanding machine learning projects.
Details
Typical total price
$0.112/hour
Features and programs
Financing for AWS Marketplace purchases
Pricing
Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
t1.micro | $0.10 | $0.02 | $0.12 |
t2.nano | $0.10 | $0.006 | $0.106 |
t2.micro AWS Free Tier Recommended | $0.10 | $0.012 | $0.112 |
t2.small | $0.10 | $0.023 | $0.123 |
t2.medium | $0.10 | $0.046 | $0.146 |
t2.large | $0.10 | $0.093 | $0.193 |
t3.nano | $0.10 | $0.005 | $0.105 |
t3.micro AWS Free Tier | $0.10 | $0.01 | $0.11 |
t3.small | $0.10 | $0.021 | $0.121 |
t3.medium | $0.10 | $0.042 | $0.142 |
Additional AWS infrastructure costs
Type | Cost |
|---|---|
EBS General Purpose SSD (gp3) volumes | $0.08/per GB/month of provisioned storage |
Vendor refund policy
Apps4Rent does not offer commercial licenses of any of the products mentioned above. The products come with open source licenses.
Legal
Vendor terms and conditions
Content disclaimer
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
Additional details
Usage instructions
Connect to your Linux instance via port no. 22 using SSH.
Please refer this article: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html Sign-in credentials: Username: ubuntu
This software does not store any sensitive customer information. This software does not require any type of data encryption configuration. programmatic system credentials and cryptographic keys are not required for this product. Dependencies version check: Python : Python 3.12.3 Pip3 : pip 24.0 Scikit-learn : scikit-learn 1.5.0
Firstly, become a superuser: sudo su
Navigate to root directory: cd /root
It is best practice to update and upgrade the machine: sudo apt update -y sudo apt upgrade -y
Command to enter python environment: source venv/bin/activate
To verify installations of Scikit-learn : pip3 show scikit-learn scikit-learn version: 1.5.0
To verify Scikit-learn installation inside python3 follow below commands: import sklearn print(sklearn.version)
Command to exit python environment: deactivate
*Below are the minimum external resources subscriber needs to have to use this product: i)An Internet Connection is required for this product to function as expected. ii)We recommend keeping your crucial data in a custom made encrypted EBS to save from termination in future.
Support
Vendor support
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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