Aeon

If you're doing anything serious with time series data, this gives you access to aeon's scikit-learn compatible toolkit for classification, regression, clustering, forecasting, and anomaly detection. The real value is in the specialized algorithms like ROCKET for fast feature extraction, DTW and other elastic distance metrics that understand temporal warping, and state-of-the-art classifiers like HIVECOTEV2. It handles both univariate and multivariate series and includes deep learning architectures like InceptionTime. The API mirrors sklearn, so pipelines and transformations work as expected. Beats cobbling together your own time series features or trying to force standard ML onto sequential data.

skills.sh installs: 324
GitHub stars: 33.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add davila7/claude-code-templates --skill aeon --agent claude-code

Installs into .claude/skills of the current project.

Files

Aeon Time Series Machine Learning

Overview

Aeon is a scikit-learn compatible Python toolkit for time series machine learning. It provides state-of-the-art algorithms for classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search.

When to Use This Skill

Apply this skill when:

Classifying or predicting from time series data
Detecting anomalies or change points in temporal sequences
Clustering similar time series patterns
Forecasting future values
Finding repeated patterns (motifs) or unusual subsequences (discords)
Comparing time series with specialized distance metrics
Extracting features from temporal data

Installation

uv pip install aeon

Core Capabilities

1. Time Series Classification

Categorize time series into predefined classes. See references/classification.md for complete algorithm catalog.

Quick Start:

from aeon.classification.convolution_based import RocketClassifier
from aeon.datasets import load_classification

# Load data
X_train, y_train = load_classification("GunPoint", split="train")
X_test, y_test = load_classification("GunPoint", split="test")

SKILL.md on GitHub