Chukudubem

africas-internet-story-visualization

air-quality-forecasting-model

Build an accurate air quality forecasting model

awesome-ml-for-cybersecurity

:octocat: Machine Learning for Cyber Security

blackbook

Blackbook of malware domains

blockmultiplication-MapReduce-Spark-

we consider using Hadoop MapReduce and Spark to implement the block-based matrix multiplication. You can assume that each matrix is stored as a text file. Each line of the file corresponds to a block of the matrix in the format of index-content. You may assume all blocks are 2-by-2 and all matrices are 6-by-6. That is each matrix is divided into 9 blocks of equal size (2-by-2 or 4 elements). The content of block is stored in a sparse format: (row index, column index, value) where row and column indexes are relative to the block. All indexes start from 1.

buzz_la

Knowledge graph of college events happening in and around Los Angeles

data-cleaning-in-jupyter

DataSynthesizer

recommendation-system-spark

trench

Machine Learning for Encrypted Network Traffic Analysis

Chukudubem/trench

Machine Learning for Encrypted Network Traffic Analysis

Chukudubem/recommendation-system-spark

Chukudubem/africas-internet-story-visualization

Chukudubem/awesome-ml-for-cybersecurity

:octocat: Machine Learning for Cyber Security

Chukudubem/blackbook

Blackbook of malware domains

Chukudubem/blockmultiplication-MapReduce-Spark-

we consider using Hadoop MapReduce and Spark to implement the block-based matrix multiplication. You can assume that each matrix is stored as a text file. Each line of the file corresponds to a block of the matrix in the format of index-content. You may assume all blocks are 2-by-2 and all matrices are 6-by-6. That is each matrix is divided into 9 blocks of equal size (2-by-2 or 4 elements). The content of block is stored in a sparse format: (row index, column index, value) where row and column indexes are relative to the block. All indexes start from 1.

Chukudubem/buzz_la

Knowledge graph of college events happening in and around Los Angeles

Chukudubem/data-cleaning-in-jupyter

Chukudubem/DataSynthesizer

Chukudubem/fatt

FATT /fingerprintAllTheThings - a pyshark based script for extracting network metadata and fingerprints from pcap files and live network traffic

Chukudubem/fbctf

Platform to host Capture the Flag competitions

Chukudubem/Girvan-Newman

This is an implementation of Girvan Newman algorithm using Spark

Chukudubem/Hierachical-Clustering

Chukudubem/INF552_DataScienceBowl2018

- Project for USC's INF 552 Machine Learning course

Chukudubem/INF554_A9

Assignment

Chukudubem/ja3

JA3 is a standard for creating SSL client fingerprints in an easy to produce and shareable way.

Chukudubem/joy

A package for capturing and analyzing network flow data and intraflow data, for network research, forensics, and security monitoring.

Chukudubem/jupyter-tips-and-tricks

Using Project Jupyter for data science.

Chukudubem/Leetcode-Unlocked

Chukudubem/maskedrcnn

Chukudubem/naivebayes

Chukudubem/nlp-qa-chatbot

Creating a Question/Answer Chatbot in Python

Chukudubem/Password-Strength-Analysis

Chukudubem/ranger

A Fast Implementation of Random Forests

Chukudubem/segram

Code and Datasets for the ARES 2021-Paper: How Private is Android’s Private DNS Setting? Identifying Apps by Encrypted DNS Traffic

Chukudubem/spl-spt

Zeek plugin to generate data on per-packet sizes and intervals

Chukudubem/Toivenen-Algorithm

Chukudubem/word_cloud

A little word cloud generator in Python

Chukudubem/zat

Zeek Analysis Tools (ZAT): Processing and analysis of Zeek network data with Pandas, scikit-learn, and Spark

Chukudubem/zeek

Zeek is a powerful network analysis framework that is much different from the typical IDS you may know.