Codebase for information theoretic shapley values to explain predictive uncertainty.This repo contains the code related to the paperWatson, D., O'Hara, J., Tax, N., Mudd, R., & Guy, I. (2023). Expl…

An interpretable probabilistic model for short-term solar power forecasting using natural gradient boosting

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

Google Research

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning …

XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification

OpenEMS - Open Source Energy Management System

Data, Benchmarks, and methods submitted to the M5 forecasting competition

Model interpretability and understanding for PyTorch

Tabler is free and open-source HTML Dashboard UI Kit built on Bootstrap

Counterfactual Explanations for Multivariate Time Series Data

TensorFlow Tutorials with YouTube Videos

Code for Machine Learning for Algorithmic Trading, 2nd edition.

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

Perform multivariate time series forecasting using LSTM networks and DeepLIFT for interpretation

A game theoretic approach to explain the output of any machine learning model.

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Atersa / Axpert Inverter python library / interface / tool