resinas

xyflow

React Flow | Svelte Flow - Powerful open source libraries for building node-based UIs with React (https://reactflow.dev) or Svelte (https://svelteflow.dev). Ready out-of-the-box and infinitely customizable.

questdb

QuestDB is an open source time-series database for fast ingest and SQL queries

ydata-profiling

1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

evidently

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

interpretable-ml-book

Book about interpretable machine learning

promptfoo

Test your prompts, agents, and RAGs. Red teaming, pentesting, and vulnerability scanning for LLMs. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.

plot

A concise API for exploratory data visualization implementing a layered grammar of graphics

EconML

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.

awesome-machine-learning-interpretability

A curated list of awesome responsible machine learning resources.

awesome-causality-algorithms

An index of algorithms for learning causality with data

nba_api

An API Client package to access the APIs for NBA.com

category_encoders

A library of sklearn compatible categorical variable encoders

feature_engine

Feature engineering package with sklearn like functionality

WikiSQL

A large annotated semantic parsing corpus for developing natural language interfaces.

Awesome-explainable-AI

A collection of research materials on explainable AI/ML

imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

CausalDiscoveryToolbox

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

xai

XAI - An eXplainability toolbox for machine learning

awesome-interpretable-machine-learning

xai_resources

Interesting resources related to XAI (Explainable Artificial Intelligence)

causalML

The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML

causallib

A Python package for modular causal inference analysis and model evaluations

DeepTables

DeepTables: Deep-learning Toolkit for Tabular data

graph-drawing-libraries

Trying to compare known graph drawing libraries

open_source_demos

A collection of demos showcasing automated feature engineering and machine learning in diverse use cases

dslp

The Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and sustainably. The process is documented in this repo.

explainx

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms8909@nyu.edu

zoomus

Python client library for the Zoom.us REST API v1 and v2

obsidian-automation

A set of scripts to help with automating tasks around the Obsidian text editor

TIHM-Dataset

TIHM: An open dataset for remote healthcare monitoring in dementia