Bytepawn - Marton Trencseni

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• Bytepawn - Marton Trencseni

  Bytepawn Marton Trencseni - Sun 20 October 2024 • Tagged with ab-testing The article illustrates how Monte Carlo simulations serve as a powerful method for exploring statistical con...

• Bytepawn - Marton Trencseni – The Full Stack Data Scientist

  What are the core skills a data scientist needs to sustainably achieve bottom-line impact, without blocking on external help from other roles?

• Bytepawn - Marton Trencseni – Category: Data

  Bytepawn I discuss why A/B testing is widely regarded as the golden standard of causal inference, using evidence from A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Ex...

• Bytepawn - Marton Trencseni – Reducing variance in A/B testing with CUPED

  I use Monte Carlo simulations of A/B tests to demonstrate CUPED, a method to use historic

• Bytepawn - Marton Trencseni – SVM with Pytorch

  I use the standard Iris dataset for supervised learning with a Support Vector Machine model using Pytorch's autograd.

• Bytepawn - Marton Trencseni – Getting Started with MLFlow

  For the last few months I’ve been using MFlow in production, specifically its Tracking component. MLFlow is an open source project for lifecycle tracking and serving of ML models, coming out of Databr...