Deep Learning

Materials prepared by 'Future Lab' (https://futurelab.creatorlink.net/)

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
1_Numpy tutorial.ipynb		1_Numpy tutorial.ipynb
2_Activation Function.pdf		2_Activation Function.pdf
2_Random Initialization.pdf		2_Random Initialization.pdf
3_Build the model by Sequential.ipynb		3_Build the model by Sequential.ipynb
3_Holdout Validation.ipynb		3_Holdout Validation.ipynb
4_Deep Learning Tutorial - Version 1.ipynb		4_Deep Learning Tutorial - Version 1.ipynb
4_Deep Learning Tutorial - Version 2.ipynb		4_Deep Learning Tutorial - Version 2.ipynb
4_Understanding dropout by numpy.ipynb		4_Understanding dropout by numpy.ipynb
5_Initialize Test.ipynb		5_Initialize Test.ipynb
5_Minmaxscaler _ standardscaler.ipynb		5_Minmaxscaler _ standardscaler.ipynb
5_Normalize Test.ipynb		5_Normalize Test.ipynb
5_Optimizer Test.ipynb		5_Optimizer Test.ipynb
6_Convolution Neural Network.ipynb		6_Convolution Neural Network.ipynb
6_RNN tutorial.ipynb		6_RNN tutorial.ipynb
7_Matplotlib 특강 1 - State-machine 기법.ipynb		7_Matplotlib 특강 1 - State-machine 기법.ipynb
7_Matplotlib 특강 2 - 객체 지향 방식.ipynb		7_Matplotlib 특강 2 - 객체 지향 방식.ipynb
7_Matplotlib 특강 3 - 2가지 방식이 혼용되는 기법.ipynb		7_Matplotlib 특강 3 - 2가지 방식이 혼용되는 기법.ipynb
8_Early Stopping.ipynb		8_Early Stopping.ipynb
8_Learning Rate Decay.ipynb		8_Learning Rate Decay.ipynb
8_The method for saving model.ipynb		8_The method for saving model.ipynb
README.md		README.md

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