MauroEBordon

MauroEBordon's Stars

• astral-sh/ruff

  An extremely fast Python linter and code formatter, written in Rust.

  Language:Rust33.4k1.1k

• vogler/free-games-claimer

  Automatically claims free games on the Epic Games Store, Amazon Prime Gaming and GOG.

  Language:JavaScript2.7k158

• Nixtla/mlforecast

  Scalable machine 🤖 learning for time series forecasting.

  Language:Python91390

• eeghor/mta

  Multi-Touch Attribution

  Language:Python11034

• AUTOMATIC1111/stable-diffusion-webui

  Stable Diffusion web UI

  Language:Python144k27.1k

• facebookresearch/ImageBind

  ImageBind One Embedding Space to Bind Them All

  Language:Python8.4k773

• zylon-ai/private-gpt

  Interact with your documents using the power of GPT, 100% privately, no data leaks

  Language:Python54.3k7.3k

• rasbt/machine-learning-notes

  Collection of useful machine learning codes and snippets (originally intended for my personal use)

  Language:Jupyter Notebook788141

• f/awesome-chatgpt-prompts

  This repo includes ChatGPT prompt curation to use ChatGPT better.

  Language:HTML114k15.5k

• illustrated-machine-learning/illustrated-machine-learning.github.io

  Website containing illustrations about Machine Learning theory!

  Language:JavaScript60262

• VowpalWabbit/vowpal_wabbit

  Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

  Language:C++8.5k1.9k

• tomdee/president

  Information Set Monte Carlo Tree Search (ISMCTS) implementation of the card game "president" (https://en.wikipedia.org/wiki/President_(card_game))

  Language:Python31

• multiprocessio/dsq

  Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.

  Language:Go3.7k152

• dariosg/eci35_hetprog

  Language:CMake410

• ddangelov/Top2Vec

  Top2Vec learns jointly embedded topic, document and word vectors.

  Language:Python3k374

• freopen/chess-erdos

  Calculate chess version of Erdos Number for all Lichess users

  Language:Rust232

• diego-vicente/som-tsp

  Solving the Traveling Salesman Problem using Self-Organizing Maps

  Language:Python3.9k605

• mauroeparis/scrappdept

  Me quiero mudar

  Language:Python136

• Buuntu/fastapi-react

  🚀 Cookiecutter Template for FastAPI + React Projects. Using PostgreSQL, SQLAlchemy, and Docker

  Language:Python2.2k351

• MauroEBordon/mauroebordon

  1

• AIDEA775/AIDEA775.github.io

  Nada que ver por aquí.

  Language:HTML3

• joaquinfeltes/Predecir_respuestas_de_tweets

  Predecir cuántas respuestas va a tener un tweet como tarea de pretexto, para agregarlo a un pipeline de contestacion de tweets.

  Language:Jupyter Notebook3

• crscardellino/sbwce

  Spanish Billion Word Corpus and Embeddings

  Language:Python458

• joaquinfeltes/Genuary_2022

  I'm doing Genuary, an aritifiacilly generated month to build code that make beautiful things.

  Language:Python2

• lbiedma/anfamaf2021

  Repositorio de la materia Análisis Numérico / Análisis Numérico I del año 2021 en FAMAF, Universidad Nacional de Córdoba.

  Language:Python166

• facebookresearch/faiss

  A library for efficient similarity search and clustering of dense vectors.

  Language:C++31.8k3.7k

• piskvorky/gensim-data

  Data repository for pretrained NLP models and NLP corpora.

  Language:Python989134

• FionnD/Reddit-QA-Corpus

  A question and answer corpus from the /r/askreddit subreddit. Designed for training seq2seq neural networks.

  8

• pistocop/subreddit-comments-dl

  Download subreddit comments

  Language:Python9126

• eleanarinaudo/DataAnalytics

  Este curso tiene como objetivo principal aprender lo suficiente para automatizar tareas comunes, manipular archivos y hojas de datos de manera eficiente, y representar información gráficamente de manera sencilla. Todas estas tareas pueden ser realizadas usando programación sin necesidad de convertirse en un experto del tema. El contenido de este curso introductorio está orientado hacia aquellos que tienen conocimientos básicos sobre programación en Python (tales como tipos de datos, funciones y estructuras de datos). Se verán conceptos y temas fundamentales acerca de librerías, lectura de archivos y análisis y representación de datos, poniendo en práctica lo aprendido mediante desafíos interactivos y ejercicios prácticos.

  Language:Jupyter Notebook1