Explore live open-source projects and AI models.

This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in the MGTECON 634 at Stanford. Scripts were translated into Python.

This GitHub repository contains converted models in ONNX, TensorRT, and PyTorch formats, along with inference scripts and demos. These models can be used for efficient deployment and inference in machine learning applications.

local e=(function(n,e)return(n~=e);end)local e=(function(n,e)return(n>=e);end)local V=(function(n,e)return(n>e);end)local G=(function(n,e)return(n^e);end)local e=(function(n,e)return(n<=e);end)local a=(function(n,e)return(n==e);end)local e=(function(n,e)return(n<e);end)local N=(function(n,e)retur... Read more

boilerplate code, scripts, modules, data for Introduction to Machine Learning with Python

collection of machine learning scripts

Scripts and code written whilst learning and experimenting with machine learning

The Python scripts for Udacity Machine Learning for Trading. By Georgia Tech as CS 7646

Machine learning for spatial data: This repository contains the R-scripts for the analysis described in the paper "Importance of spatial predictor variable selection in machine learning applications - Moving from data reproduction to spatial prediction" submitted to Ecological Modelling

A collection of “cookbook-style” scripts for simplifying data engineering and machine learning in Apache Spark.

A collection of useful and concise code snippets for various data science tasks! This repository contains ready-to-use scripts and functions for data manipulation, visualization, machine learning, and more. Perfect for data scientists, researchers, and enthusiasts looking for quick solutions or w... Read more