aviyashchin
Data-driven founder. 2x exit in Public Markets. Dad. Human. Ex Carbon and Climate activist @ Engine1, Two Sigma & IBM Watson Research.
United States
aviyashchin's Stars
Significant-Gravitas/AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
gpt-engineer-org/gpt-engineer
Platform to experiment with the AI Software Engineer. Terminal based. NOTE: Very different from https://gptengineer.app
astral-sh/ruff
An extremely fast Python linter and code formatter, written in Rust.
Pythagora-io/gpt-pilot
The first real AI developer
shap/shap
A game theoretic approach to explain the output of any machine learning model.
joaomdmoura/crewAI
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
joonspk-research/generative_agents
Generative Agents: Interactive Simulacra of Human Behavior
openai/evals
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
ItzCrazyKns/Perplexica
Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI
varunshenoy/GraphGPT
Extrapolating knowledge graphs from unstructured text using GPT-3 🕵️♂️
ray-project/llm-numbers
Numbers every LLM developer should know
astriaai/headshots-starter
py-why/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.
btw-so/open-source-alternatives
List of open-source alternatives to everyday SaaS products.
fern-api/fern
Input OpenAPI. Output SDKs and Docs.
NannyML/nannyml
nannyml: post-deployment data science in python
py-why/causal-learn
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
pymc-labs/CausalPy
A Python package for causal inference in quasi-experimental settings
BiomedSciAI/causallib
A Python package for modular causal inference analysis and model evaluations
Technion-Kishony-lab/data-to-paper
data-to-paper: Backward-traceable AI-driven scientific research
microsoft/causica
expectedparrot/edsl
Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.
AliciaCurth/CATENets
Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
helliun/causal-chains
Library for creating causal chains using language models.
sotopia-lab/awesome-social-agents
A collection of works that investigate social agents, simulations and their real-world impact in text, embodied, and robotics contexts.
yapms/yapms
Yet Another Political Map Simulator
jacksonjude/USA-Election-Map
An interactive US presidential, senate, house, and governor map for election results and projections. Written in HTML/CSS/JS
koconder/synthetic-user-research
Example Notebook for Synthetic User Research with Persona Prompting and Autonomous Agents
tmk1221/frameSmith
Subconscious-ai/sublime
🧠Behavior Change as a Service🌞