LibESN

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Statsmodels: statistical modeling and econometrics in Python

A python library for user-friendly forecasting and anomaly detection on time series.

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

Probabilistic time series modeling in Python

Merlion: A Machine Learning Framework for Time Series Intelligence

Time series forecasting with PyTorch

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.