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ab-trap

This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

agent_based_model

Example Meme Propagation

allennlp

An open-source NLP research library, built on PyTorch.

allennlp-models

Officially supported AllenNLP models

ap-gcn

Adaptive Propagation Graph Convolutional Network

applications

scripts for 688

attackgraphgeneration

awesome-graph-attack-papers

Adversarial attacks and defenses on Graph Neural Networks.

chinese_sentiment_analysis

Tutorial for Chinese Sentiment analysis with hotel review data

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

cnn-exercise

Convolutional Neural Network exercise code and supporting documents.

code

Compilation of R and Python programming codes on the Data Professor YouTube channel.

coursera_class

crime-prediction

CS281 Final Project to develop a new ML Model for predicting incidents of crime.

cropyield

Creates a data pipeline from the Famine Land Data Assimilation DataSet (FLDAS) to seed model terrain and assess the potential crop yield for a variety of crops.

cyber-attack-attribution-with-machine-learning

Cyber attack attribution is the process of attempting to trace back a piece of code or malware to a perpetrator of a cyberattack. As cyber attacks have become more prevalent, cyber attack attribution becomes more valuable. The process of cyber attack attribution can be done using reverse engineering. From the metadata of the malware executable file, we can gather data such as date of creation, variable names used, and what library calls are imported. This information can be used as features for attribution analysis. We need to extract the features from malware that can be used for attribution and analyse them using some technique to attribute the attacks.

data

Data Sets for Machine Learning Practice

datasciencecoursera

This repo houses works from taking Data Science Specialization at JHU.

deeplearning-ids

Network Intrusion Detection System using Deep Learning Techniques

designing-ml-intrusion-detection-system

Source Code for 'Designing a Machine Learning Intrusion Detection System' (video) by Emmanuel Tsukerman

discogan

Official implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

discogan-pytorch

PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

english_chinese_machine_translation_baseline

tensor2tensor usage

es-acled

Elastic search index for the Armed Conflict Location and Event Data Project (ACLED) from Asia and Africa in the same Elastic Search index.

es-gtd

The Global Terrorism Database (GTD) is an open-source database including information on terrorist events around the world from 1970 through 2016 (with annual updates planned for the future).

exdata_plotting1

Plotting Assignment 1 for Exploratory Data Analysis

fortified-networks

Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations

gcn

Implementation of Graph Convolutional Networks in TensorFlow

get-and-clean-data-course-project