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Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models

Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics

Scalable machine 🤖 learning for time series forecasting.

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

RRDtool 1.x - Round Robin Database

ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.

Bringing financial analysis to the tidyverse

Quantitative Financial Modelling Framework

Time-series database

ML powered analytics engine for outlier detection and root cause analysis.

A python library for time-series smoothing and outlier detection in a vectorized way.

Time series analysis in the `tidyverse`

SiriDB is a highly-scalable, robust and super fast time series database. Build from the ground up SiriDB uses a unique mechanism to operate without a global index and allows server resources to be added on the fly. SiriDB's unique query language includes dynamic grouping of time series for easy analysis over large amounts of time series.

Accumulo backed time series database

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

Financial market technical analysis & indicators in Julia

Extensible time series class that provides uniform handling of many R time series classes by extending zoo.

Time-aware tibbles

Detect trend in time series, drawdown, drawdown within a constant look-back window , maximum drawdown, time underwater.

AI-powered NBA game outcome predictor that uses advanced team stats and trend-based features to forecast winners and track model performance

Quantitative systematic trading strategy development and backtesting in Julia

Time series market data

Use Python like a spreadsheet!

Python interface to Brazilian Central Bank web services

NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

Time series implementation for the Julia language focused on efficiency and flexibility

R interface to Brazilian Central Bank web services

A modular single-molecule analysis interface

Here, the most popular Electric Load Forecasting datasets are collected centrally. Feel free to support this work. 🔥

Automatic discovery of non-trivial statistical truths from 500+ public time series — mutual information, Granger causality, FDR correction