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lpp-campaign

Ethereum contract for liquid pledging campaign plugin

lpp-capped-milestone

LiquidPledging plugin to manage capped milestones

lsh

C minhash lsh education-orient

lstmvis

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

lua-travis-example

For experiments with travis-ci

luaffifb

FFI package for Lua 5.1 and Lua 5.2

ludwig

Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.

machine

Machine management for a container-centric world

machine-learning-workshop

machine_learning

magic

CSS3 Animations with special effects

maitlibs.xamarinforms.imagetinteffect

Helps you tint your images in Xamarin Forms iOS, Android & UWP

makisu

Fast and flexible Docker image building tool, works in unprivileged containerized environments like Mesos and Kubernetes.

mass

MASS: Masked Sequence to Sequence Pre-training for Langauge Generation

material

Material is an animation and graphics framework that allows developers to easily create beautiful applications.

material-controls-for-ios

Many Google Material Design Controls for iOS native application

material-remixer-ios

Remixer helps teams use and refine design specs by providing an abstraction for these values that is accessible and configurable from both inside and outside the app itself

materialdesigncocoa

Material Design UI Components for Cocoa

materialkit

Material design components for iOS written in Swift

mathematical-expression-recognition

Recognition of Online Handwritten Mathematical Expressions

mathematics_dataset

This dataset code generates mathematical question and answer pairs, from a range of question types at roughly school-level difficulty.

mathfax

sick of coding no longer being a challenge? Are you festive? Come on in

mathfinder

Various document layout analysis techniques are employed in order to enhance the accuracy of optical character recognition (OCR) in document images. Type-specific document layout analysis involves localizing and segmenting specific zones in an image so that they may be recognized by specialized OCR modules. Zones of interest include titles, headers/footers, paragraphs, images, mathematical expressions, chemical equations, musical notations, tables, circuit diagrams, among others. False positive/negative detections, oversegmentations, and undersegmentations made during the detection and segmentation stage will confuse a specialized OCR system and thus may result in garbled, incoherent output. In this work a mathematical expression detection and segmentation (MEDS) module is implemented and then thoroughly evaluated. The module utilizes the open source OCR software, Tesseract and the machine learning library, DLib.

mathquill

Easily type math in your webapp

mathsteps

Step by step math solutions for everyone

mbprogresshud

MBProgressHUD + Customizations

mdcquickselect

Categories to quickly select the "n-th most" element, or the "n most" elements in an array.

mdcswipetochoose

Swipe to "like" or "dislike" any view, just like Tinder.app. Build a flashcard app, a photo viewer, and more, in minutes, not hours!

memfinder-ocr

OCR for internet meme images

mern-cli

A cli tool for getting started with MERN