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ml_investment

Investment tools

ml_poetry

Multimedia art: The synthesis of machine-generated poetry and virtual landscapes

ml_project_template

cookiecutter template for DS projects

mm

mm

mmailer

The purpose of Mmailer is to allow the sending of bulk email through regular smtp providers, like gmail.

mmd-gan

Training MMD GANs.

mmdb2json

A script to dump a MMDB ( MaxMind ) binary database to JSON.

mmdetect

Intel ME Manufacturing Mode Detection Tools

mmdnn

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

mmdvm-dissector

A Wireshark dissector for the MMDVM protocol

mmetokendecrypt

Decrypts and extracts iCloud and MMe authorization tokens on Apple macOS / OS X. No user authentication needed, no dependencies.

mmhdan

Calculate fingerprints of a website for OSINT search

mmid-cnn-analysis

mmm-ipcam

Display ipcam feed on MagicMirror

mmosoft.facebook.sdk

This api using your user email and password to like page or join group rather than using graph api.

mmosoft.instagram.sdk

Instagram API without OAuth

mmppsampler

Efficient implementation of the Gibbs sampler by Fearnheard and Sherlock (2006) for the Markov modulated Poisson process that uses 'C++' via the 'Rcpp' interface. Fearnheard and Sherlock (2006) proposed an exact Gibbs-sampler for performing Bayesian inference on Markov Modulated Poisson processes. This package is an efficient implementation of their proposal for binned data. Furthermore, the package contains an efficient implementation of the hierarchical MMPP framework, proposed by Clausen, Adams, and Briers (2018), that is tailored towards inference on network flow arrival data and extends Fearnheard and Sherlock's Gibbs sampler. Both frameworks harvests greatly from routines that are optimised for this specific problem in order to remain scalable and efficient for large amounts of input data. These optimised routines include matrix exponentiation and multiplication, and endpoint-conditioned Markov process sampling. Both implementations require an input vector that contains the binned observations, the length of a binning interval, the number of states of the hidden Markov process, and lose prior hyperparameters. As a return, the user receives the desired number of sample trajectories of the hidden Markov process as well as the likelihood of each trajectory.

mmtrace

mmTrace: Millimeter Wave Propagation Simulation

mmutils

Tools for working with MaxMind GeoIP csv and dat files

mnemonic-maltego

Maltego Local Transform to use mnemonic Passive DNS - https://passivedns.mnemonic.no/

mnemosyne

A Generic Windows Memory Scraping Tool

mnemosyne-1

Normalizer for honeypot data.

mnist

Quickly test classifiers on the MNIST dataset

mnist-gan

Generative Adversarial Networks for the MNIST dataset

mnist-scanner

Machine learning

mnist_brain

Work in progress; The "MNIST" of Brain Digits; Given the brain signal(s) of 2 seconds each, captured with the stimulus of seeing a digit (from 0 to 9) and thinking about it, determine what the digit is

mnistdemo

Test MNIST classifiers from your browser

mnkira

mnmlurl

🔗 Minimal URL - Modern URL shortener with support for custom alias & can be hosted even in GitHub pages [DEPRECATED]

mnp

My new passport