Scikit learn

If you are looking for a quick way to get up and running with scikit-learn on AWS, check this out. kCloudHubs offers a ready-to-launch Ubuntu 24.04 image with the latest scikit-learn (version 1.8.0 at the time of writing). It's basically the complete open-source machine learning library, plus some nice extras, all optimised for the AWS Cloud Marketplace.

Scikit-learn is one of the go-to Python libraries for machine learning. It provides solid tools for classification and regression, clustering, dimensionality reduction, model selection, and data preprocessing. It plays perfectly with NumPy, SciPy, and matplotlib, so you get a clean, consistent way to build and run ML workflows without a ton of hassle.

Key Highlights

• Supervised learning goodies like logistic regression, support vector machines (SVM), decision trees, random forests, and more.
• Unsupervised options such as K-Means clustering, DBSCAN, and Principal Component Analysis (PCA).
• Strong model evaluation and tuning features - think cross-validation, grid search, and a bunch of scoring metrics to help you dial in the best performance.

This AMI is super straightforward: launch it directly from the AWS Marketplace, get a fresh Ubuntu 24.04 environment with scikit-learn pre-installed, and you're good to go for any ML project. It's kept clean and always up-to-date, with free basic maintenance included. If you need hands-on help, updates, or troubleshooting, kCloudHubs offers optional paid support plans.

Related Options on the Marketplace

There are a couple of similar bundles worth checking out:

• NumPy, Pandas, Scikit-learn & Gradio on Ubuntu 22.04 This one stacks the full scientific Python toolkit (NumPy, Pandas, Matplotlib) plus Gradio so you can whip up interactive web demos for your models super fast. Great if you want data analysis + quick sharing.
• Hospital Readmission Predictor A ready-made, domain-specific solution built on scikit-learn. It takes EMR data, DRG codes, and billing information to predict 30-day hospital readmission risk and returns a probability score. Perfect for healthcare ops teams who want results without building everything from scratch.

All these run on Ubuntu, come with scikit-learn core APIs, and are Marketplace-ready (just launch and pay AWS usage fees). The standalone scikit-learn image keeps things minimal and flexible for general use. The Gradio bundle adds data tools and a nice UI layer. The hospital one delivers a pre-trained pipeline tailored to healthcare.

Pick whichever fits your workflow - whether you are prototyping models, analyzing data, demoing to stakeholders, or solving a specific industry problem like readmission risks. Everything is optimised for AWS, easy to scale, and backed by optional support if you want it.