Stars
Causal Inference and Discovery in Python by Packt Publishing
Uplift modeling and causal inference with machine learning algorithms
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
Easily control Intel p-state driver on Linux
Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization"
🚀 A self-hostable personal dashboard built for you. Includes status-checking, widgets, themes, icon packs, a UI editor and tons more!
Turn (almost) any Python command line program into a full GUI application with one line
A unified framework for machine learning with time series
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Probabilistic modelling and uncertainty quantification library
automatic differentiation made easier for C++
Interesting resources related to XAI (Explainable Artificial Intelligence)
Code for "Testing Robustness Against Unforeseen Adversaries"
Companion code for "Modern Computational Finance: AAD and Parallel Simulations" (Antoine Savine, Wiley, 2018)
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
Scalnyx / simplx
Forked from Tredzone/simplxC++ development framework for building reliable cache-friendly distributed and concurrent multicore software
Lime: Explaining the predictions of any machine learning classifier