Padarn Wilson's repositories
bootsteps
step-by-step tutorial on how to implement basic bootstrap analyses
Causal-Inference-1
Causal Inference 1 Mixtape Session taught by Scott Cunningham
functorch
functorch is a prototype of JAX-like composable function transforms for PyTorch.
pytorch_geometric
Graph Neural Network Library for PyTorch
pytorch_sparse
PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations
dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
dowhy
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.
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.
flink-on-k8s-operator
Kubernetes operator for managing the lifecycle of Apache Flink and Beam applications.
folium
Python Data. Leaflet.js Maps.
incubator-airflow
Apache Airflow (Incubating)
jsonparser
One of the fastest alternative JSON parser for Go that does not require schema
kube-capacity
A simple CLI that provides an overview of the resource requests, limits, and utilization in a Kubernetes cluster
kubeflow-aws
Kustomize manifest to deploy kubeflow pipelines in AWS
langchain
🦜🔗 Build context-aware reasoning applications
Open3D
Open3D: A Modern Library for 3D Data Processing
OpenSfM
Open source Structure-from-Motion pipeline
pipelines
Machine Learning Pipelines for Kubeflow
probability
Probabilistic reasoning and statistical analysis in TensorFlow
pyro
Deep universal probabilistic programming with Python and PyTorch
python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
serve
Serve PyTorch models in production
survival
Survival package for R
time-series-dataset
:wrench: Easy-to-use PyTorch Dataset object for multivariate time series :wrench:
werkzeug
A flexible WSGI implementation and toolkit