Francy Lisboa's repositories
Youtube-Audio-Transcriber-Summarizer
Youtube-Audio-Transcriber/Summarizer is a Python script that extracts audio from YouTube videos, transcribes it using OpenAI's Whisper ASR API, and summarizes the content with OpenAI's GPT-3 API, providing concise insights from video content for quick understanding and analysis.
public-apis
A collective list of free APIs
micro-agent
A tiny implementation of an autonomous agent powered by LLMs (OpenAI GPT-4)
awesome-conformal-prediction
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.
ai-code-translator
Use AI to translate code from one language to another.
the-algorithm
Source code for Twitter's Recommendation Algorithm
imitation_learning_from_language_feedback
This repository contains some of the code used in the paper "Training Language Models with Langauge Feedback at Scale"
BrowserGPT
Command your browser with GPT
GPPPT
A simple one file python script that executes AI processes defined in YML.
chatblade
A CLI Swiss Army Knife for ChatGPT
neura
Neura is an open-source virtual assistant powered by GPT 3.5 Turbo. It provides real-time responses to user queries by integrating internet search capabilities. Examples include weather forecasts and cryptocurrency prices.
webR-quarto-demos
Experiments with generating a standalone Quarto Document using Web R
ck-FARM
SoftwareX
EconChattR
Fine tuning ChatGPT on EconTalk transcripts
riffusion-app
Stable diffusion for real-time music generation (web app)
webGROR
This project aims to compile the statistical language R into WASM for use in a browser, via Emscripten.
SerpentAI
Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
materias
Reproduza as matérias do Pindograma!
Simulation-HCF
R Code for Running Honest Causal Forests on Simulated Data
causalml
Uplift modeling and causal inference with machine learning algorithms
modified_causa_forest_paper
Replication repository for "High Resolution Treatment Effects Estimation: Uncovering Effect Heterogeneities with the Modified Causal Forest"
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.