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An Example of Graph Convolutional Networks

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Adversarial Validation

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AdaNet - Adaptive Structural Learning of Artificial Neural Networks

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Machine Learning Security

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Implementing Git in Data Science

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Overview of GANs - Part III

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Overview of GANs - Part I

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Bayesian Additive Regression Trees

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Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

Controlled experiments are run on the Citeseer citation graph to understand how GCNs work

How to use Adversarial Validation to diagnose overfitting problems

A paper review of Google's AdaNet AutoML technique, which learns the optimal neural network structure

Exploring the vulnerabilities of ML models from attack by bad actors. They're more fragile than you might think

Some thoughts on how to apply version control when conducting experiments

Learning Disentangled Representations: an introduction to InfoGAN

An introduction to Generative Adversarial Networks

A paper review of BART, which is the Bayesian approach to Additive Tree models

A paper review on using Random Forests to estimate causal impact

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