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TIHM: An open dataset for remote healthcare monitoring in dementia
Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line …
Interesting resources related to XAI (Explainable Artificial Intelligence)
Trying to compare known graph drawing libraries
A collection of research materials on explainable AI/ML
DeepTables: Deep-learning Toolkit for Tabular data
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
An API Client package to access the APIs for NBA.com
A collection of demos showcasing automated feature engineering and machine learning in diverse use cases
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 go…
A set of scripts to help with automating tasks around the Obsidian text editor
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
An index of algorithms for learning causality with data
The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalAI
A large annotated semantic parsing corpus for developing natural language interfaces.
XAI - An eXplainability toolbox for machine learning
QuestDB is a high performance, open-source, time-series database
A concise API for exploratory data visualization implementing a layered grammar of graphics
A Python package for modular causal inference analysis and model evaluations
A library of sklearn compatible categorical variable encoders
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 cust…
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.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Feature engineering and selection open-source Python library compatible with sklearn.
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 @…
Book about interpretable machine learning
Python client library for the Zoom.us REST API v1 and v2
A curated list of awesome responsible machine learning resources.
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.