Setup and customize deep learning environment in seconds.
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Updated
Mar 25, 2026 - Python
Setup and customize deep learning environment in seconds.
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.
Keras package for region-based convolutional neural networks (RCNNs)
GPU-accelerated Deep Learning on Windows 10 native
The On-Ramp to Deep Learning
Bounding box detection of drones (small scale quadcopters) with CNTK Fast R-CNN
This POC is using CNTK 2.1 to train model for multiclass classification of images. Our model is able to recognize specific objects (i.e. toilet, tap, sink, bed, lamp, pillow) connected with picture types we are looking for. It plays a big role in a process which will be used to classify pictures from different hotels and determine whether it's a…
Machine Comprehension Train on MSMARCO with S-NET Extraction Modification
This sample project shows off how to prepare and deploy to Azure Web Apps a simple Python web service with an image classifying model produced in CNTK (Cognitive Toolkit) using FasterRCNN
Deep learning library that builds on and extends Microsoft CNTK
A python implementation for a CNTK Fast-RCNN evaluation client
Deep Learning (Keras) Models Deployment using SQL databases
reinforcement learning with cntk
A CNTK implementation of CapsNet based on Geoffrey Hinton's paper Dynamic Routing Between Capsules
Categorical DQN from 'A distributional Perspective on Reinforcement Learning'
Boundary Equilibrium Generative Adversarial Networks (BEGAN) Implementation in Microsoft Cognitive Toolkit (CNTK)
Person, Age, Gender and Emotion recognition using CNTK and MXNet.
Contains training and prediction scripts for CNTK Faster-RCNN Object Detection
This repo contains python files that describe different machine learning libraries such as the pytorch, tensorflow, keras, scikit and caffe
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