eco3
Follow
Stars
scikit-learn: machine learning in Python
The fundamental package for scientific computing with Python.
A generative world for general-purpose robotics & embodied AI learning.
Bayesian Modeling and Probabilistic Programming in Python
A python library for user-friendly forecasting and anomaly detection on time series.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports comp…
A unified framework for machine learning with time series
Probabilistic time series modeling in Python
NeuralProphet: A simple forecasting package
The machine learning toolkit for time series analysis in Python
An intuitive library to add plotting functionality to scikit-learn objects.
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Exploratory analysis of Bayesian models with Python
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
An intuitive library to extract features from time series.
An extension of XGBoost to probabilistic modelling
Flexible time series feature extraction & processing
Reliability engineering toolkit for Python - https://reliability.readthedocs.io/en/latest/
An extension of LightGBM to probabilistic modelling
Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
Python package for missing-data imputation with deep learning