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oddstream-1

oddstream {Outlier Detection in Data STREAMs} :fish: :fish: :fish: :fish: :tropical_fish: :fish: :fish: :fish: :fish: :fish: :fish: :fish: :fish:

one-pixel-attack

PyTorch implementation of "One Pixel Attack for Fooling Deep Neural Networks"

one-pixel-attack-keras

Keras reimplementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet

onion-service-usability

Research project about understanding how Tor users interact with onion services

onionscan

OnionScan is a free and open source tool for investigating the Dark Web.

online-category-learning

ML algorithm for real-time classification

opensketch

simulation and netfpga code

osint_public

owl

packetanalyzer

Analyze network traffic captures with statistical metrics / measurements

padchat-sdk

永久免费 微信ipad、微信mac协议，可实现微信80%功能；支持62数据登录、扫码登录、收发朋友圈、查看朋友圈、微信建群、微信拉人进群、微信公众号阅读、微信消息收发、微信附近的人定位、微信添加好友、微信红包接收、微信防撤回、分享小程序、微信加粉、微信收藏、微信标签等

paican

Implementation of "Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure".

paif

Multivariate Time Series Anomaly Detection Technique Code

pam18-inlogwetrust

Links and updates for the dataset of our PAM'18 paper "In Log We Trust: Revealing Poor Security Practices with Certificate Transparency Logs and Internet Measurements"

pig-scripting-examples

Examples of use of pig scripting languages capabilities

pipesocks

A pipe-like SOCKS5 tunnel system.

playcap

Performs playback of tcpdump, windump, Wireshark, and libpcap files.

pomdps.jl

MDPs and POMDPs in Julia - An interface for working with discrete and continuous, fully and partially observable Markov decision processes.

port-client-ip-monitor

Use to monitor shadowsocks client ip

predicting-customer-response

Did this project for Data Science. These data are a subset of data from a targeted marketing campaign. Each data record describes a targeted consumer by various attributes. Had to answer the following questions-a) (5 Marks) What is the structure of the file? What are the attributes/fields? How many customers are there? (Can be answered easily at the command line, without Python.) b) (5 Marks) Do any two customers have the same name? If so, list the duplicated name(s). c) (5 Marks) Sometimes data values are missing and programs in the data processing pipeline fill in special values that can screw up analysis. How many rows have value -9999? Do not consider them in any further processing. d) (5 Marks) RFA_2F and RFA_2A are marketing codes summarizing the recency and frequency of historical customer response. What values do they take and what is the frequency of each value in the data? What values does WEALTH_INDEX take? e) (5 Marks) TARGET_B describes whether this customer responded (1) or did not respond (0) to the campaign. What proportion of the targeted consumers responded? f) (10 Marks) Create a dendrogram. How many clusters are evident? Justify your answer. g) (10 Marks) Plot the distributions of WEALTH_INDEX for the responders and non-responders on one graph to show the similarities and differences. Use a histogram. What is the difference in the graphs from plotting percents versus counts on the y-axis? (Hint: in the matplotlib "hist", look at "normed=True" and look at different numbers of "bins".) h) (5 Marks) Alphabetize the records by the NAME field. Number them from 1 at the beginning of the alphabet. Do not print them all out. Just print out alphabetized records 1-10 and alphabetized records 20,000-20,010. i) (5 Marks) Redo part (h), except alphabetize by the individual's *last name*. j) (40 Marks) Split the data into an appropriate Training and Test set. Using the Training data, train 3 predictive models (choose 3 appropriate classifiers) for TARGET_B (whether the customer responds). Using the Test set, compare their performance using ROC plots and Area Under the Curves (AUC). Which is the "best" according to your analysis?

predicting_stock_prices

predictron

Tensorflow implementation of "The Predictron: End-To-End Learning and Planning"

privacyadversarial-regularization

prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

proxy2

HTTP/HTTPS proxy in a single python script

psprite

pycharm-color-scheme

color scheme for pycharm IDE

pycharm-color-schemes

A bunch of color schemes (Solarized Light, Zen and Art) for the PyCharm python IDE (http://www.jetbrains.com/pycharm).

pycharm-twilight

A Pycharm port of the Textmate theme Twilight.

pydata_bcn_networkx

Materials for the NetworkX workshop at PyData Barcelona 2017 conference