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Marcelo's Projects

scylla icon scylla

NoSQL data store using the seastar framework, compatible with Apache Cassandra

sde-interview-questions icon sde-interview-questions

Most comprehensive list :clipboard: of tech interview questions :blue_book: of companies scraped from Geeksforgeeks, CareerCup and Glassdoor.

sears icon sears

Code for "Semantically Equivalent Adversarial Rules for Debugging NLP Models"

selenium-crawler icon selenium-crawler

Sometimes sites make crawling hard. Selenium-crawler uses selenium automation to fix that.

sense icon sense

SENSE: a Shared Encoder Network for Scene-flow Estimation

sensei icon sensei

distributed realtime searchable database

sentinel icon sentinel

A lightweight powerful flow control component enabling reliability and monitoring for microservices

sentry icon sentry

Sentry is cross-platform application monitoring, with a focus on error reporting.

serenata-de-amor icon serenata-de-amor

🕵 Artificial Intelligence for social control of public administration

serf icon serf

Service orchestration and management tool.

serritor icon serritor

Serritor is an open source web crawler framework built upon Selenium and written in Java

server icon server

MariaDB server is a community developed fork of MySQL server. Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry.

serverless icon serverless

⚡ Serverless Framework – Build web, mobile and IoT applications with serverless architectures using AWS Lambda, Azure Functions, Google CloudFunctions & more! –

serverless.tf icon serverless.tf

serverless.tf is an opinionated open-source framework for developing, building, deploying, and securing serverless applications and infrastructures on AWS using Terraform.

sgan icon sgan

Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018

shap icon shap

A game theoretic approach to explain the output of any machine learning model.

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