samuel-gerstein

samuel-gerstein's Stars

• dair-ai/Prompt-Engineering-Guide

  🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

  Language:MDX51.3k5632075k

• adap/flower

  Flower: A Friendly Federated AI Framework

  Language:Python5.3k42598907

• ouckah/Summer2025-Internships

  Collection of Summer 2025 tech internships!

  2.8k2331.5k96

• bsovs/Fall2024-Internships

  Collection of Fall 2023 tech internships!

  1.3k35223145

• AshwinRJ/Federated-Learning-PyTorch

  Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

  Language:Python1.3k936452

• pysentimiento/pysentimiento

  A Python multilingual toolkit for Sentiment Analysis and Social NLP tasks

  Language:Jupyter Notebook567164965

• GoldinGuy/UltimateGitResource

  📚 The ultimate collection of git commands and resources to power up your programming!

  39510046

• cenpy-devs/cenpy

  Explore and download data from Census APIs

  Language:Python183910444

• kenfehling/latex-cheatsheet

  Template for a compact LaTeX Cheatsheet I made some years ago.

  Language:TeX17560124

• jtleider/censusdata

  Download data from Census API

  Language:Python139124129

• abdelrhmanelruby/Spotify-Recommendation-System

  Spotify Recommendation System Using Spotify Million Playlist Dataset

  Language:Jupyter Notebook554010

• sandarshsridhar/wiz-spotify-connected

  A service to dance 😉 your Wiz lights to playing Spotify music.

  Language:TypeScript44599

• saranshmanu/Federated-Learning

  Federated Learning is a distributed machine learning approach which enables model training on a large corpus of decentralised data. The repository tutorial for using PySyft for distributed training of Machine Learning model.

  Language:HTML423222

• mkucz95/encrypted_ai_finance

  Credit Approval Classification Deep Learning Model using Differential Drivacy, Secure Multi-Party Computation, and Federated Learning

  Language:HTML24235

• vaseline555/Federated-Learning-with-Flower

  Simple simulation of federated learning (FedAvg) using Flower framework

  Language:Python22104

• asymworks/pyairnow

  Python Client for AirNow API

  Language:Python13223

• Fustincho/UD-Private-In-bed-Posture-Classification

  Project entry for the Secure and Private AI Challenge, hosted by Udacity and sponsored by Facebook (May - August, 2019)

  Language:Jupyter Notebook9404

• exabrial/sonic-pi-beats

  Just dabbling into music with SonicPI

  Language:Ruby4301

• fresleven/CarleChain

  CS128H project

  Language:Rust40

• lrizvi/latex-refsheet

  latex exam reference sheet (cheat sheet)

  Language:TeX4000

• ApoorvaJain13/Household-Power-Prediction

  Predicted the Global Active Power of a house on hourly basis

  Language:Jupyter Notebook30

• smakonin/HUE.dataset

  Scripts of the the The Hourly Usage of Energy Dataset for Buildings in British Columbia (HUE dataset) https://doi.org/10.7910/DVN/N3HGRN

  Language:Python3200

• elddc/locationlocationlocation

  A project for CodeADA 2022

  Language:Python2202

• kuihao/KuihaoFL

  This is a record of an experiment using Flower (https://flower.dev/) to implement various federated learning algorithms.

  Language:Jupyter Notebook2100

• buddejul/metrics-cheatsheet

  Template for a compact LaTeX Cheatsheet I made some years ago.

  Language:TeX1001

• uirphack/2024

  2024 University of Illinois Research Park Hackathon

  1000