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godel's Introduction

Godel

Exploring Testing Sharing

explaing model https://christophm.github.io/interpretable-ml-book/

Decorators: https://www.thecodeship.com/patterns/guide-to-python-function-decorators/

github upstream management: https://medium.com/sweetmeat/how-to-keep-a-downstream-git-repository-current-with-upstream-repository-changes-10b76fad6d97

Uncertainty

https://blog.evjang.com/2018/12/uncertainty.html

Keras

model entity embedding + model concate

add new layer based on pretained model

ODE

https://blog.acolyer.org/2019/01/09/neural-ordinary-differential-equations/amp/

Math

  1. VAE

Practical Machine Learning

Dropout:

https://medium.com/@bingobee01/a-review-of-dropout-as-applied-to-rnns-72e79ecd5b7b

Deep Learning Theory

Bayesian Neural Nets

Recurrent Neural Nets

Autoencoder

GMM and EM

Case Study

  1. CNN

Attention model

Kaggle: upzip https://www.kaggle.com/c/diabetic-retinopathy-detection/discussion/45994

Graph Neural nets:

https://towardsdatascience.com/a-gentle-introduction-to-graph-neural-network-basics-deepwalk-and-graphsage-db5d540d50b3

book:

  1. **传统地权制度及其

godel's People

Contributors

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