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Mark Hillebrand edited this page Oct 18, 2016 · 14 revisions

Recurrent Neural Networks with CNTK and applications to the world of ranking
GRUs on CNTK with BrainScript
Deep Crossing on CNTK
Sequence to Sequence – Deep Recurrent Neural Networks in CNTK – Part 1
Sequence to Sequence – Deep Recurrent Neural Networks in CNTK – Part 2 – Machine Translation

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Toggle table of contents Pages 144

Home
Activation Functions
Adapt a model I trained on one task to another
Articles
Associate an id with a prediction
Avoid AddSequence Exception
Avoid the error CURAND failure 201
Baseline Metrics
BatchNormalization
Binary Operations
BrainScript Network Builder
BS Basic Concepts
BS Expressions
BS Functions
BS Model Editing
Build a constant 3D tensor
CloneFunction
CNTK 1bit SGD License
CNTK 2.0 Examples
CNTK 2.0 Python API
CNTK 2.0 Setup
CNTK 2.0 Setup from Sources
CNTK Binary Download and Configuration
CNTK Binary Download and Manual Installation
CNTK Docker Containers
CNTK Evaluate Hidden Layers
CNTK Evaluate Image Transforms
CNTK Evaluate Multiple Models
CNTK Evaluation Overview
CNTK FAQ
CNTK Library API
CNTK on Azure
CNTK Python known issues and limitations
CNTK usage overview
CNTK_1_5_Release_Notes
CNTK_1_6_Release_Notes
CNTK_1_7_1_Release_Notes
CNTK_1_7_2_Release_Notes
CNTK_1_7_Release_Notes
CNTK_2_0_Beta_1_Release_Notes
CNTKTextFormat Reader
Coding Guidelines
Command line parsing rules
Compatible dimensions in reader and config
Conference Appearances
Config file overview
Continue training from a previously saved model
Contributing to CNTK
ConvertDBN command
Convolution
Deal with the 'No Output nodes found' error
Deal with the error 'No node named 'x'; skipping'
Deal with the error 'Reached the maximum number of allowed errors'
Debugging CNTK source code in Visual Studio
Debugging CNTK's GPU source code in Visual Studio
Deep Crossing on CNTK
Developing and Testing
Do early stopping
Dropout
Dropout during evaluation
Enabling 1bit SGD
Evaluate a model in an Azure WebApi
Evaluate my newly trained model but output the activations at an intermediate layer
Examples
Express a gating mechanism
Express a softmax over a dynamic axis
Express a softmax with a temperature parameter
Express the error rate of my binary classifier
Full Function Reference
Gather and Scatter
Get nice syntax highlighting for BrainScript config files
Get started in sequence to sequence modelling
GRUs on CNTK with BrainScript
Hands On Labs Image Recognition
Hands On Labs Language Understanding
How do I
How do I run Eval in Azure
How do I use a trained model as a feature extractor
How to Test
HTKMLF Reader
If Operation
Image reader
Implement Zoneout
Inputs
KDD 2016 Tutorial
Layer wise training
Layers Library Reference
Layers Reference
LM sequence reader
Loss Functions and Metrics
LU sequence reader
Managed Evaluation Interface
Monitor the error on a held out set during training
Monitor the error on a held out set during training or do Cross Validation (CV) during training
Multiple GPUs and machines
Native Evaluation Interface
News
NuGet Package
Nuget Package for Evaluation
Object Detection using Fast R CNN
OptimizedRNNStack
Parameters And Constants
Plot command
Pooling
Post Batch Normalization Statistics
Presentations
Reader block
Recommended CNTK 2.0 Setup
Records
Recurrent Neural Networks with CNTK and applications to the world of ranking
Reduction Operations
Sequence to Sequence – Deep Recurrent Neural Networks in CNTK – Part 1
Sequence to Sequence – Deep Recurrent Neural Networks in CNTK – Part 2
Sequence to Sequence – Deep Recurrent Neural Networks in CNTK – Part 2 – Machine Translation
Sequential
Setup CNTK on Linux
Setup CNTK on Windows
Setup CNTK on your machine
SGD Block
Simple Network Builder
Special Nodes
Specify multiple label streams with the HTKMLFReader
Test Configurations
Times and TransposeTimes
Top level commands
Top level configurations
Train a DSSM (or a convolutional DSSM) model
Train a multilabel classifier
Train a regression model on images
Train with a multitask objective
Train, Test, Eval
Troubleshoot CNTK
Tutorial
Tutorial2
Tutorials
Tutorials, Examples, etc..
UCI Fast Reader
Unary Operations
Understanding and Extending Readers
Use an already trained network multiple times inside a larger network
Use built in readers with multiple inputs
Using CNTK with BrainScript
Using CNTK with multiple GPUs and or machines
Variables

Home
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FAQ
How do I...
Troubleshoot CNTK

Getting Started

Setting up CNTK for Use
CNTK Usage Overview
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How to use CNTK

Using CNTK with Python
Using CNTK with BrainScript

Using CNTK Models in Your Code

Overview
Nuget Package for Evaluation
C++ Evaluation Interface
C# Evaluation Interface
Evaluating Hidden Layers
C# Image Transforms for Evaluation
C# Multi-model Evaluation
Evaluate in Azure

Advanced topics

Command Line Parsing Rules
Top-level Commands
Plot Command
ConvertDBN Command
Baseline Metrics

Licenses

CNTK License
CNTK 1bit-SGD License

Source Code & Development

Setup for Windows
Setup for Linux
Developing and Testing
Enabling 1bit SGD
CNTK Production Test Configurations
How to contribute to CNTK

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