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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 graphical models and potential outcomes frameworks.

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.

A Python library for audio data augmentation. Useful for making audio ML models work well in the real world, not just in the lab.

Free, easy, portable audio engine for games

Factor programming language

? Data-driven render automation for After Effects

A curated list of awesome Xamarin.Forms libraries and resources

Fast audio data augmentation in PyTorch. Inspired by audiomentations. Useful for deep learning.

a comprehensive collection of video game tech analysis resources

Real-time voice-changer for voice-chat, etc. Will support many different voice-filters and features in the future. ?