Results for “time-series”

Forecast any univariate time series (sales, sensors, energy, vitals, weather) zero-shot using Google's TimesFM foundation model, with point forecasts and prediction intervals from CSV, DataFrame, or array inputs.

Runs time series machine learning tasks—classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search—using the scikit-learn compatible aeon toolkit.

Fit statistical models (OLS, GLM, ARIMA, mixed models) with detailed diagnostics, residuals, and inference for econometrics and time series analysis.

Reads and preprocesses 5-minute stock candlestick CSV data, then clusters the time series using tslearn's TimeSeriesKMeans, including data cleaning, percentage change calculation, model training, saving, and representative sample extraction.

Execute KQL queries and manage Azure Data Explorer resources for fast, scalable big data analytics on log, telemetry, and time series data.

Write, review, debug, or interpret Python statistical models using statsmodels, including formulas, regression, GLM, time series, robust covariance, diagnostics, prediction intervals, and inference.

Perform time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search using a scikit-learn compatible Python toolkit.

Predict continuous values from temporal sequences using aeon's time series regressors, covering convolutional, deep learning, distance-based, feature-based, hybrid, interval-based, and shapelet-based approaches.

Detect anomalies in time-series data using the Azure AI Anomaly Detector SDK for Java, with support for univariate and multivariate analysis, model training, and inference.

Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.

Build collaborative forensic incident timelines using Timesketch to ingest, normalize, and analyze multi-source event data for attack chain reconstruction and investigation documentation.

Build forensic super timelines from disk images using Plaso (log2timeline) and triage them in Timesketch.

Zero-shot univariate time-series forecasting with Google's TimesFM foundation model, producing point forecasts and prediction intervals from CSV/DataFrame/array inputs, with a preflight system checker for RAM/GPU. Use to forecast any univariate series (sales, sensors, energy, vitals, weather) without training a custom model. Part of the AlterLab Academic Skills suite.

Manipulates and analyzes data with pandas, including DataFrames, group operations, and time series.

Guides scaling Qdrant vector search with time-based data rotation using shard rotation, collection rotation, or filter-and-delete strategies.

Perform efficient pandas DataFrame operations for data analysis, manipulation, and transformation with production-grade patterns.

Automate InfluxDB Cloud operations like querying, managing buckets, and writing data through Composio's toolkit via Rube MCP.

Compresses long K-line (candlestick) data into a fixed-length sequence using OHLC aggregation rules and applies min-max normalization.

Build interactive, accessible charts, graphs, and data dashboards using Recharts, D3, or Victory. Use when the user says "chart", "graph", "data visualization", "analytics dashboard", "metrics display", "D3", "Recharts", "time-series", or "data display".

Kalshi prediction market data (prices, odds, orderbooks, trades). Use for prediction markets, Kalshi, betting odds, election and sports betting, market forecasts. Provides real-time market data, event series information, and comprehensive trading analytics.