Page Index - microsoft/CNTK GitHub Wiki
207 page(s) in this GitHub Wiki:
- Home
- Welcome
- 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