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1. Commits on Mar 2, 2020

   • Hello World for tf2.0

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2. Commits on Mar 1, 2020

   • upgrade to tf.net 1.15.0

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3. Commits on Feb 10, 2020

   • fix Fully Connected Neural Network

     Oceania2018

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   • fix CnnInYourOwnData.

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   • fix MNIST CNN

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4. Commits on Feb 9, 2020

   • Add test and prediction for Text CNN sample.

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5. Commits on Feb 3, 2020

   • Use NumSharp compact version.

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6. Commits on Jan 20, 2020

   • upgrade SharpCV to 0.3.0.

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7. Commits on Jan 18, 2020

   • add YOLOv3, but not working.

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8. Commits on Jan 17, 2020

   • modify data download url.

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9. Commits on Jan 6, 2020

   • change load images process:Load local images asynchronously,use queue,improve train efficiency

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10. Commits on Jan 4, 2020

    • rename to SciSharp STACK Examples

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11. Commits on Jan 1, 2020

    • upgrade tf.net

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12. Commits on Dec 26, 2019

    • Add incompleted object detection example.

      

      Esther2013

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      Oceania2018

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    • Detect From Video

      

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    • compile in Ubuntu

      

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13. Commits on Dec 21, 2019

    • replace file CnnInYourOwnData.cs

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      pepure

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      Oceania2018

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    • replace files

      

      pepure

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14. Commits on Dec 16, 2019

    • change netcore version to 3.1

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    • Merge remote-tracking branch 'upstream/master'

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    • add necessary NuGet packages :

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15. Commits on Dec 15, 2019

    • fix mat to array method bug

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    • CNN in your own data

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    • fix mat to array method bug

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    • CNN in your own data

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16. Commits on Dec 10, 2019

    • fix LogisticRegression example

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17. Commits on Dec 4, 2019

    • upgrade to TF.NET v0.13.0.

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18. Commits on Nov 28, 2019

    • validate saved model for mnist cnn.

      Oceania2018

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    • merge

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19. Commits on Nov 27, 2019

    • define freeze_model function.

      Oceania2018

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    • import from checkpoint for mnist cnn in python

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    • Merge branch 'master' of https://github.com/SciSharp/TensorFlow.NET-Examples

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    • update MNIST CNN python code.

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20. Commits on Nov 26, 2019

    • Finished MNIST LSTM.

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21. Commits on Nov 25, 2019

    • Added LSTM RNN example.

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