About Zak Jost

Zak Jost is Research/Data Scientist at Amazon, applying data science and machine learning to fight fraudsters at Amazon Web Services. His focus is on building lean end-to-end solutions that deliver large, sustainable business impact in a principled way. He enjoys the infrastructure engineering as much as the analysis and modeling. He blogs also at Towards Data Science.

Zak Jost Posts (5)

• Adversarial Validation Overview - 13 Feb 2020
  
  Learn how to implement adversarial validation that builds a classifier to determine if your data is from the training or testing sets. If you can do this, then your data has issues, and your adversarial validation model can help you diagnose the problem.
• InfoGAN - Generative Adversarial Networks Part III - 30 Nov 2017
  
  In this third part of this series of posts the contributions of InfoGAN will be explored, which apply concepts from Information Theory to transform some of the noise terms into latent codes that have systematic, predictable effects on the outcome.
• Generative Adversarial Networks — Part II - 17 Nov 2017
  
  Second part of this incredible overview of Generative Adversarial Networks, explaining the contributions of Deep Convolutional-GAN (DCGAN) paper.
• Overview of GANs (Generative Adversarial Networks) – Part I - 10 Nov 2017
  
  A great introductory and high-level summary of Generative Adversarial Networks.
• Getting Started with Python for Data Analysis - 05 Jul 2017
  
  A guide for beginners to Python for getting started with data analysis.