borysrybak

borysrybak's Stars

• tensorflow/tensorflow

  An Open Source Machine Learning Framework for Everyone

  Language:C++186k7.6k39.8k74.2k

• github/gitignore

  A collection of useful .gitignore templates

  162k3.4k083.1k

• explosion/spaCy

  💫 Industrial-strength Natural Language Processing (NLP) in Python

  Language:Python29.8k5625.6k4.4k

• fastai/fastai

  The fastai deep learning library

  Language:Jupyter Notebook26.2k6061.8k7.5k

• matterport/Mask_RCNN

  Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

  Language:Python24.6k5812.8k11.7k

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook22.6k2412.5k3.3k

• microsoft/CNTK

  Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

  Language:C++17.5k1.3k3.3k4.3k

• mrgloom/awesome-semantic-segmentation

  :metal: awesome-semantic-segmentation

  10.5k441252.5k

• dotnet-architecture/eShopOnWeb

  Sample ASP.NET Core 8.0 reference application, powered by Microsoft, demonstrating a layered application architecture with monolithic deployment model. Download the eBook PDF from docs folder.

  Language:C#10.1k4793365.5k

• opencv/opencv_contrib

  Repository for OpenCV's extra modules

  Language:C++9.4k3821.5k5.8k

• github/semantic

  Parsing, analyzing, and comparing source code across many languages

  Language:Haskell9k396271454

• qqwweee/keras-yolo3

  A Keras implementation of YOLOv3 (Tensorflow backend)

  Language:Python7.1k1987123.4k

• 1adrianb/face-alignment

  :fire: 2D and 3D Face alignment library build using pytorch

  Language:Python7k1723111.3k

• microsoft/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.

  Language:Python5.8k181617964

• navdeep-G/samplemod

  Language:Python4.8k10801.5k

• Azure/MachineLearningNotebooks

  Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

  Language:Jupyter Notebook4.1k1.9k1.4k2.5k

• microsoft/code-with-engineering-playbook

  This is the playbook for "code-with" customer or partner engagements

  Language:Dockerfile2.2k2.3k420587

• mrharicot/monodepth

  Unsupervised single image depth prediction with CNNs

  Language:Python2.2k92252631

• experiencor/keras-yolo2

  Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).

  Language:Jupyter Notebook1.7k67437784

• keras-team/keras-preprocessing

  Utilities for working with image data, text data, and sequence data.

  Language:Python1k43180444

• karolzak/keras-unet

  Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks

  Language:Python3391338108

• microsoft/TagAnomaly

  Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

  Language:R32030861

• microsoft/Cognitive-Face-Windows

  Windows SDK for the Microsoft Face API, part of Cognitive Services

  Language:C#1778436161

• aaxwaz/Fraud-detection-using-deep-learning

  Language:Jupyter Notebook11313159

• olgaliak/active-learning-detect

  Active learning + object detection

  Language:Python10082933

• augmentedstartups/mask-rcnn

  Video Tutorial Series on Mask RCNN

  Language:Python921667

• Daniel-Krzyczkowski/WindowsIoT-AzureIoT

  Windows IoT Core code samples.

  Language:C7417

• ikivanc/Bot-Framework-v4-with-Azure-Search

  This is a demo for Azure Search with Bot Framework v4 C# application.

  Language:HTML4100

• normalian/BotDirectlineApp-Java

  This is a Direct Line API Sample of Bot Framework

  Language:Java31

• kritcs18-zz/Neural-Style-Transfer

  This is a keras implementation of neural style described in the paper by Gatys et.al. The main objective of neural style is to generate an image that is as close as in terms of content to the base image and as close as in terms of style to the style image.

  Language:Jupyter Notebook22