985 Open source projects that are alternatives of or similar to DataScience_ArtificialIntelligence_Utils

Predictive AI layer for existing databases.

Fast approximate Shapley values in R

FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)

Remaining Useful Life (RUL) estimation of Lithium-ion batteries using deep LSTMs

(Explainable AI) - Learning Non-Monotonic Logic Programs From Statistical Models Using High-Utility Itemset Mining

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.

A Python library for time series forecasting

In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).

Explaining the output of machine learning models with more accurately estimated Shapley values

Debugging, monitoring and visualization for Python Machine Learning and Data Science

Various methods for generating synthetic data for data science and ML

Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.

The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".

Fit interpretable models. Explain blackbox machine learning.

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations

An open-source, low-code machine learning library in Python

Code for Java Deep Learning Cookbook

PyTorch implementation of TSception

Essential NLP & ML, short & fast pure Python code

Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020

Integration examples of Tanker's client-side encryption SDKs

ExpMRC: Explainability Evaluation for Machine Reading Comprehension

Synthetic Minority Over-Sampling Technique for Regression

Time series annotation library.

R interface for Fixed Effect Models

Sample applications demonstrating usages of Progress® Telerik® FiddlerCore Embedded Engine.

LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION

Example Apps for Polished

Gaussian dynamic Bayesian networks structure learning and inference based on the bnlearn package

⚙️ Solving sudoku using Deep Reinforcement learning in combination with powerful symbolic representations.

run a multitude of classifiers on you data and get an AUC report

several utilities to help wrangle COVID-19 data into a time-series format

Python machine learning package based on sklearn API for multivariate data processing and statistical analysis of symmetric positive definite matrices via Riemannian geometry

In this repository you can find many different, small, projects which demonstrate regression techniques using python programming language

Examples to demonstrate how to use PipeCD

⏰📊✨Laravel Time Series - Provides an API to create and maintain data projections (statistics, aggregates, etc.) from your Eloquent models, and convert them to time series.

Template codes and examples for Python machine learning concepts

⏰ This R package provides the tools to perform standard and robust wavelet variance analysis for time series (signal processing). Among others, aside from computing the wavelet variance and cross-covariance (classic and robust), the package provides inference tools (e.g. confidence intervals) and plotting tools allowing to perform some visual an…

REPO MOVED TO https://repetere.github.io/jsonstack-model - Deep Learning Classification, Clustering, LSTM Time Series and Regression with Tensorflow

Shows how to use wxWidgets controls only by programming code (c++17).

Materials about my talk around Eclipse Milo at EclipseCon Europe 2017

Simple Genetic Programming for Symbolic Regression in Python3

ZestDB

A random forest

The Understanding Gradle video series introduces the concepts of the Gradle Build Tool one-by-one in short videos.

Introduction to Machine Learning with Time Series at PyData Festival Amsterdam 2020

Detecting and Predicting Forest Cover Change in Pakistani Areas Using Remote Sensing Imagery

library of numerical methods using Armadillo

Machine Learning Finite State Machine Models from Data with Genetic Algorithms

(117th place - Top 26%) Deep learning using Keras and Spark for the "Store Item Demand Forecasting" Kaggle competition.

A chess library for PHP.

Example code. You probably don't want to use any of this.

A generalizable application framework for segmentation, regression, and classification using PyTorch

framework for developing machine (and deep) learning models for structured data

Examples - aah Go web framework

MATLAB code for Relevance Vector Machine using SB2_Release_200.

Some practice shaders in Godot

Python library for Ceteris Paribus Plots (What-if plots)