Series of SQL exercise working with databases, using Google BigQuery to scale to massive datasets taught by educators in Kaggle.com

Permite abrir e manipular arquivos massivos de texto/dados cujo seria impossivel abrir em um computador, por exemplo um arquivo de texto de +20gb, permite manipular o arquivo pegando apenas as linhas necessárias sem travar o computador por falta de memória.

Building node2vec algorithm

Command line tool to quickly generate a lot of files in a lot of directories

gipa -- compression/decompression tool to package compress and encode massive archive files with floating-point data

Map Reduce program to suggest new friends based on count of mutual friends

Lab assignments for the Analysis of Massive Data Sets course @ FER, University of Zagreb

Building a Bloom Filter on English dictionary words

This project facilitates the efficient mass registration of products using Rabbit MQ, managing loads exceeding 50,000 products.

Algorithms for Massive Datasets (AMD) -- Market-baskets analysis project

📺 Content Recommendation System for the Netflix Prize Challenge with Collaborative Filtering.

The project is based on the analysis of the "IBM Transactions for Anti Money Laundering" dataset published on Kaggle. The task is to implement a model which predicts whether or not a transaction is illicit, using the attribute "Is Laundering" as a label to be predicted.

Stream, parse, manipulate and transform extremly large data ( can be 1 GB or 1TB ) in NodeJS without any process block, memory overflow or bottle neck with peak performance. And also show it in UI with the help of webStreams

TF-Package: Multiple-Input Multiple-Output Keras Data-Generator for massive and complex datasets

This repository contains a LaTeX file that generates a PDF document comprising comprehensive notes for the course "Algorithms for Massive Datasets"

Calculate statistical measures of one column in big data Datasets with these simply Hadoop Application

University lab exercises with processing big data.

word count in Spark

Building PageRank algorithm on Web Graph around Stanford.edu using NetworkX python library