stjordanis Goto Github PK

imaging

Imaging is a simple image processing package for Go

imaging-research

imagiz

Fast and none blocking live video streaming over network with OpenCV and ZMQ.

imaku

A danmaku shooter in Erlang/OpenGL

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

imdb---scrapper

Scraps title and other information of the movies for different parameters

imdb_data

IMDB data analysis

imdbreviewclassification

imet-collection

imet-collection-2019

Solution to iMet Collection 2019 - FGVC6 on Kaggle

img_classification_pk_pytorch

Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)

imgaug

Image augmentation for machine learning experiments.

imglab

To speedup and simplify image labeling/ annotation process with multiple supported formats.

imgui

Dear ImGui: Bloat-free Immediate Mode Graphical User interface for C++ with minimal dependencies

imgui-sfml

ImGui binding for use with SFML

imgui.net.fsharp

FSharp wrapper for ImGui.NET wrapper for cimgui wrapper for the awesome imgui!

imguizmo.quat

ImGui GIZMO widget - 3D object manipulator / orientator

imgur-downloader

imgur album downloader

imitation-learning-dagger-torcs

A Simple Example for Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env

imitation-learning-from-imperfect-demonstration

[ICML 2019] Implementation of "Imitation Learning from Imperfect Demonstration"

imitation-learning-from-observation

iml

iml: interpretable machine learning R package

iml-course

Course about interpretable machine learning

iml-talk

Talk about interpretable machine learning

immer

Postmodern immutable and persistent data structures for C++ — value semantics at scale

imms

High Performance, Immutable Data Structures for .NET

immunoaizer

A computational framework for cell distribution and gene mutation prediction in tumor microenvironment

immunopipe

immunotherapy-response-prediction

Data for the paper 'Prediction of clinical response to checkpoint blockade immunotherapy is improved with ensembling'

imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).