Overview
Scikit-learn on Ubuntu 24.04 with maintenance support by ATH. This is a repackaged open source software product wherein additional charges apply for support. Scikit-learn is a widely used open-source machine learning library in Python, designed to provide a user-friendly interface for implementing various machine learning algorithms and data preprocessing techniques. Built on top of popular Python libraries like NumPy, SciPy, and Matplotlib, Scikit-learn offers a comprehensive suite of tools for tasks such as classification, regression, clustering, dimensionality reduction, model selection, and preprocessing. Its simplicity, combined with extensive documentation and active community support, makes Scikit-learn an ideal choice for both beginners and experts in the field of data science and machine learning.
Highlights
- Scikit-learn provides implementations for a broad array of machine learning algorithms, including support vector machines (SVM), random forests, k-means clustering, and linear regression, among others.
- The library includes powerful tools for data preprocessing, such as scaling, normalization, encoding categorical variables, and handling missing data, ensuring that datasets are well-prepared for model training.
- Scikit-learn offers various methods for evaluating model performance, including cross-validation, metrics for classification and regression, and hyperparameter tuning techniques like grid search, which help in selecting the best model for a given task.
Details
Typical total price
$0.17/hour
Features and programs
Financing for AWS Marketplace purchases
Pricing
Free trial
Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
t2.micro AWS Free Tier | $0.01 | $0.012 | $0.022 |
t2.small | $0.07 | $0.023 | $0.093 |
t2.medium | $0.07 | $0.046 | $0.116 |
t2.large | $0.07 | $0.093 | $0.163 |
t2.xlarge | $0.07 | $0.186 | $0.256 |
t2.2xlarge | $0.07 | $0.371 | $0.441 |
t3.nano | $0.07 | $0.005 | $0.075 |
t3.micro AWS Free Tier | $0.07 | $0.01 | $0.08 |
t3.small | $0.07 | $0.021 | $0.091 |
t3.medium | $0.07 | $0.042 | $0.112 |
Additional AWS infrastructure costs
Type | Cost |
|---|---|
EBS General Purpose SSD (gp3) volumes | $0.08/per GB/month of provisioned storage |
Vendor refund policy
No Refund
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
Try one unit of this product for 5 days. There will be no software charges for that unit, but AWS infrastructure charges still apply. Free Trials will automatically convert to a paid subscription upon expiration and you will be charged for additional usage above the free units provided.
Additional details
Usage instructions
Connect your virtual machine via SSH using username "ubuntu". To Access Scikit-learn use below commands to access it: Step 1: To Update the package and to Initialize the Scikit-learn Database use below command:
- sudo su
- sudo apt update Step 2: Activate the Virtual Environment and check the version using below command:
- virtualenv myenv
- source myenv/bin/activate
- python check_sklearn.py Now its activated and you can access it. Sample is below. Step 3: Create a file sample named "test_sklearn.py" and test it using below commands:
- nano test_sklearn.py
- python test_sklearn.py You will see the Output as : "Accuracy: 1.00"
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.
Similar products
