Repository Index

Beautiful animated placeholders for showing loading of data

• swift
• placeholder
• animation
• gradient

Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux

• deep-learning
• deep-neural-networks
• gradient-descent
• automatic-differentiation

A .NET library that provides fast, accurate and automatic differentiation (computes derivative / gradient) of mathematical functions.

• mathematical-modelling
• automatic-differentiation
• mathematics
• math

High performance gradient boosting for Ruby

• machine-learning
• lightgbm
• rubyml

Get a recipe to cook today, based on the ingredients you have at home.

• hacktoberfest
• recipes
• self-hosted

Ruby Scoring API for PMML

• ruby-gem
• pmml
• random-forest
• classification

Veganify is a modern webapp that allows you to easily scan EAN barcodes to check if a product is vegan-friendly. With a database of over 3 million products, you can quickly find out if your favorite foods and products are suitable for a vegan diet.

• scanner
• barcode
• html5
• javascript

Classification and Gradient-based Localization of Chest Radiographs using PyTorch.

• fine-tuning
• vgg16
• resnet18
• densenet121

A curated collection of splendid gradients made in Kotlin

Want to crack passwords faster by using a wordlist that fits your 'target audience'? Use WikiRaider.

• wordlist
• wikipedia
• dictionary
• attack

CatBoost a fast, scalable, high performance Gradient Boosting on Decision Trees library. Golang using Cgo for blazing fast inference CatBoost Model 🚀

• cgo
• golang
• deep-learning
• gradient-boosting

This is a module for framer.js that makes it easy to create static linear/radial gradients. Want them to animate? I welcome pull requests.

A custom View for Android Java / Xamarin.Android that creates an iridescent effect on top of images.

• xamarin
• xamarin-android
• android-java
• iridescence

A Framer module for applying gradients to layers and animating them.

Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.