Lecture slides and quizzes for Leskovec, Rajaraman, and Ullman's "Mining of Massive Datasets" Stanford course

Solutions to the Exercises found in Mining Massive Datasets

Spearheading the integration of extraterrestrial resources with Pi Network, ExoGenesis provides a platform for developing space-based mining algorithms, satellite-based infrastructure, and interplanetary communication protocols, opening new frontiers for decentralized networks.

[Homeworks] CS246: Mining Massive Data Sets, Stanford / Spring 2021

电子科技大学2022级研究生课程《大数据分析与挖掘》，包含课件、作业、电子书。

Basic implementation of algorithms described in the Coursera Mining Massive datasets class. For educational purposes only.

MMD solutions for Stanford CS246 in R

Sketch code along the reading of Mining Massive Datasets

Data mining algorithms with Python

Mining of Massive Datasets - Stanford

Recommendation systems, Twitter Streaming, SON Algorithm,Frequent Itemsets, , BFR, AMS, Bloom Filter, Community Detection using Modularity, Girvan-Newman Algorithm implementation in Spark-Python.

Analysis of Reddit Comments for Mining Massive Datasets at the Technical University of Munich

An Introduction to Mining of Social Network Graphs based on Rajaraman, Anand, and Jeffrey D. Ullman. Mining of massive datasets. Chapter 10

GP-Alpha-Miner is a high-performance, industrial-grade quantitative factor mining framework. It combines the search capabilities of Genetic Programming (GP) with the parallel computing power of GPUs, aiming to automatically discover Alpha factors with high ICIR and low turnover rates from massive datasets.

Modern technologies for Machine Learning and Mining of Massive Datasets

Exercises on the field of Mining massive datasets

find similar text files quickly

Learning Stanford MiningMassiveDatasets in Coursera

Coursera: Mining Massive Datasets (Sep 2014)

Mining Massive Datasets @ https://class.coursera.org/mmds-001

Coursera Mining Massive Datasets

CS246: Mining Massive Data Sets Solutions

Solution to the programming assingments for the IN2323 spring course Mining Massive Datasets on the Technical University of Munich.

Code for assignments for this Coursera MOOC

Learnings from Stanford's Mining Massive Datasets course

Ben Will and Spencer toying on the amazon's hadoop implementation to play with concepts in the mining of massive datasets book (http://infolab.stanford.edu/~ullman/mmds.html).

This repository covers DSCI553, focusing on data mining—a crucial skill for analyzing massive datasets. The course explores algorithms for uncovering patterns in data, with a practical emphasis. Students will learn to apply data mining techniques to solve real-world problems.

4 methodologies to find similar documents. Different methodologies can be used based on the case at hand. This repository can be used to find similar documents among billions of documents.

My implementations of Stanford's CS246 Mining Massive Datasets course homeworks

Backend for identification of IoT use cases in massive Twitter datasets using text mining