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hyptrails

hyrise

HYRISE In-Memory Hybrid Storage Engine

i2

I²: Interactive Real-Time Visualization for Streaming Data

iarn

Implementation for Interacting Attention-gated Recurrent Networks (IARN)

ibis

Productivity-centric Python big data framework for high performance at Hadoop-scale, with first-class integration with Impala. Co-founded by the creator of pandas

ibis-demo

Demo notebook of Ibis for "Spark + Python + Dita science Festival"

ic_ba_2020

icebucket

UNRELEASED. An opinionated framework for analytics-on-write on event streams using key-value storage

iclr15

Sentiment Analysis with Ensemble

icv-sbr

Benchmarking of Session-based Recommendation Approaches

id-match-engine

Id match grails app based off of Oyster Match Algorithm Libs

idao-2020-sat-id

ideepa

Attention-based CNN for predicting RBP binding sites

idmlib

Data mining libraries for all iZENECloud projects

idomaar

CrowdRec reference framework

ids_assortment_optimization

ijcnn19ensemble

Deep Neural Network Ensembles for Time Series Classification

imcs

In-Memory Columnar Store extension for PostgreSQL

imhotep

Imhotep is a large-scale analytics platform built by Indeed.

immens

Real-Time Visual Querying of Big Data

impala_cookbook

Cookbook to install Impala using Chef

implementation_variational-auto-encoder

Simple implementation of Variational Autoencoder

implicit

Fast Python Collaborative Filtering for Implicit Datasets

implicit-data-based-recommendation-system

A music recommendation system based on the number and type of songs that the user listened to | Achieved ~90% AUC for ~40,000 users and ~100,000 artists

implicit-mf

Implicit matrix factorization as outlined in http://www2.research.att.com/~yifanhu/PUB/cf.pdf.

imprints

simd enabled column imprints

improved-gan

code for the paper "Improved Techniques for Training GANs"

impyla

Python client and Numba-based UDFs for Impala

inca

LASSO, mixed effects modeling, LR analyses

incremental-algorithms-for-spark-mllib

This project intends to add more incremental algorithm support for Spark MLlib, including Naive Bayes, Collaborative filtering, SVM, freqent pattern mining, etc.