vvkishere

explaining-in-style

graph_maker

looper

A resource list for causality in statistics, data science and physics

anchor

Code for "High-Precision Model-Agnostic Explanations" paper

autogen

A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap

awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

BERT-NER

Pytorch-Named-Entity-Recognition-with-BERT

cleanlab

The standard package for data-centric AI and machine learning with label errors, finding mislabeled data, and uncertainty quantification. Works with most datasets and models.

ConvoKit

ConvoKit is a toolkit for extracting conversational features and analyzing social phenomena in conversations. It includes several large conversational datasets along with scripts exemplifying the use of the toolkit on these datasets.

crewAI-examples

Examples I was exploring for agent frameworks

developer-roadmap

Interactive roadmaps, guides and other educational content to help developers grow in their careers.

devika

Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective. Devika aims to be a competitive open-source alternative to Devin by Cognition AI.

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.

fine-grained-event-classification

research repo for fine grained event classification

gecko-app

A web application that interfaces two GEC systems.

hora

🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .

latent-scope

A scientific instrument for investigating latent spaces

neuralcoref

✨Fast Coreference Resolution in spaCy with Neural Networks

neuspell

NeuSpell: A Neural Spelling Correction Toolkit

nlpaug

Data augmentation for NLP

professional-programming

A collection of learning resources for curious software engineers

pymc

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

qlib

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.

Resources-Front-End-Beginner

💯 The most essential list of resources for Front-End beginners (🇺🇸 🇬🇧 🇨🇦 & 🇫🇷)

serverless-template

For deployment of models

service-streamer

Boosting your Web Services of Deep Learning Applications.

SKU110K-DenseDet

A state of art detector for densely packed scenes dataset SKU-110K

small-text

Active Learning for Text Classification in Python

transcriptionstream

turnkey self-hosted offline transcription and diarization service with llm summary