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CNTK move to Cuda8

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Mark Hillebrand edited this page Nov 25, 2016 · 6 revisions

The Cognitive Toolkit and Cuda 8

Toggle table of contents Pages 206

Home
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
BatchNormalization
Binary Operations
BrainScript Activation Functions
BrainScript and Python Understanding and Extending Readers
BrainScript and Python Performance Profiler
BrainScript Basic Concepts
BrainScript CNTKBinary Reader
BrainScript CNTKTextFormat Reader
BrainScript Command line parsing rules
BrainScript Config file overview
BrainScript epochSize and Python epoch_size in CNTK
BrainScript expressions
BrainScript Full Function Reference
BrainScript Functions
BrainScript HTKMLF Reader
BrainScript Image reader
BrainScript Layers Reference
BrainScript LM sequence reader
BrainScript LU sequence reader
BrainScript minibatchSize and Python minibatch_size_in_samples in CNTK
BrainScript Model Editing
BrainScript Network Builder
BrainScript Reader block
BrainScript Reader block.1
BrainScript Reader block.2
BrainScript Reader block.3
BrainScript SGD Block
BrainScript Top level configurations
BrainScript Train, Test, Eval
BrainScript UCI Fast Reader
Breaking changes in Master compared to beta15
Build your own image classifier using Transfer Learning
CloneFunction
CNTK 1bit SGD License
CNTK 2.0 Beta Highlights
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 Configuration
CNTK Docker Containers
CNTK Eval Examples
CNTK Evaluate Hidden Layers
CNTK Evaluate Image Transforms
CNTK Evaluate Multiple Models
CNTK Evaluation Overview
CNTK Evaluation using cntk.exe
CNTK FAQ
CNTK Library API
CNTK Library Evaluation on Linux
CNTK Library Evaluation on Windows
CNTK Library Evaluation Overview
CNTK Library Managed API
CNTK Library Native Eval Interface
CNTK model format
CNTK move to Cuda8
CNTK on Azure
CNTK Python known issues and limitations
CNTK Shared Libraries Naming Format
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_10_Release_Notes
CNTK_2_0_Beta_11_Release_Notes
CNTK_2_0_Beta_12_Release_Notes
CNTK_2_0_Beta_15_Release_Notes
CNTK_2_0_Beta_1_Release_Notes
CNTK_2_0_Beta_2_Release_Notes
CNTK_2_0_Beta_3_Release_Notes
CNTK_2_0_Beta_4_Release_Notes
CNTK_2_0_Beta_5_Release_Notes
CNTK_2_0_Beta_6_Release_Notes
CNTK_2_0_Beta_7_Release_Notes
CNTK_2_0_Beta_8_Release_Notes
CNTK_2_0_Beta_9_Release_Notes
CNTK_2_0_RC_1_Release_Notes
CNTK_2_0_RC_2_Release_Notes
CNTK_2_0_RC_3_Release_Notes
Coding Guidelines
Compatible dimensions in reader and config
Conference Appearances
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
EvalDll Evaluation on Linux
EvalDll Evaluation on Windows
EvalDll Evaluation Overview
EvalDll Managed API
EvalDll Native API
Evaluate a model in an Azure WebApi
Evaluate my newly trained model but output the activations at an intermediate layer
Examples
Feedback Channels
Gather and Scatter
GRUs on CNTK with BrainScript
Hands On Labs Image Recognition
Hands On Labs Language Understanding
How do I
How do I Adapt Models in BrainScript
How do I Adapt models in Python
How do I Deal with Errors in BrainScript
How do I Deal with Errors in Python
How do I Evaluate Models in BrainScript
How do I Evaluate models in Python
How do I Express Things in BrainScript
How do I Express Things In Python
How do I in BrainScript
How do I in Python
How do I Read Things in BrainScript
How do I Read Things in Python
How do I run Eval in Azure
How do I Train Models in BrainScript
How do I Train models in Python
How do I use a trained model as a feature extractor
How to Test
If Operation
Image Auto Encoder Using Deconvolution And Unpooling
Inputs
KDD 2016 Tutorial
Layers Library Reference
Loss Functions and Metrics
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
News
News 2016
NuGet Package
Object Detection using Fast R CNN
OptimizedRNNStack
Parameters And Constants
Plot command
Pooling
Post Batch Normalization Statistics
Presentations
project a 1D input of dim inputDim to a 1D output of dim outputDim
Put labels and features in separate files with CNTKTextFormatReader
Reasons to Switch from TensorFlow to CNTK
Recommended CNTK 2.0 Setup
Records
Recurrent Neural Networks with CNTK and applications to the world of ranking
Reduction Operations
Relate alpha, beta1, beta2 and epsilon to learning rate and momentum in adam_sgd optimizer
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 BuildProtobuf VS15
Setup Buildzlib VS15
Setup CNTK on Linux
Setup CNTK on Windows
Setup CNTK on your machine
Setup CNTK Python Tools For Windows
Setup CNTK with script on Windows
Setup Linux Binary Manual
Setup Linux Binary Script
Setup Linux Python
Setup Migrate VS13 to VS15
Setup Test Python
Setup Windows Binary Manual
Setup Windows Binary Script
Setup Windows Binary Script Options
Setup Windows Devinstall Script Option
Setup Windows Python
Simple Network Builder
Special Nodes
Specify multiple label streams with the HTKMLFReader
Test Configurations
Times and TransposeTimes
Top level commands
Troubleshoot CNTK
Tutorial
Tutorial2
Tutorials
Tutorials, Examples, etc..
Unary Operations
Update 1bit SGD Submodule Location
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 Keras
Using CNTK with multiple GPUs and or machines
Using TensorBoard for Visualization
Variables
Windows Environment Variables
WWW 2017 Tutorial

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Iteration Plans

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