Guido Tapia

Guido Tapia

September 22, 2016

Download XGBoost Windows x64 Binaries and Executables

[Edit]: It appears the XGBoost team has fixed pip builds on Windows. There are also nightly artifacts generated. As such, I hereby turn off my nightly builds. [Edit]: These builds (since 19th of Dec 2016) now have GPU support. If this causes any issu ...

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Guido Tapia

December 6, 2016

Introducing XGBoost.Net - .Net wrappers for the awesome XGBoost library

Introducing XGBoost.Net - .Net wrappers for the awesome XGBoost library XGBoost is a big part of our Machine Learning and Predictive Analytics toolkit here at PicNet. We use it almost heavily for our proof of concept and prototype work and it is alwa ...

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Guido Tapia

March 5, 2018

How to Work with Machine Learning

A very common problem I find in the industry is senior managers not fully understanding how best to utilize Machine Learning technologies to help their business. A common misconception is that these projects should be treated the same as traditional ...

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Guido Tapia

March 8, 2018

When is an Organisation Ready to Benefit from Machine Learning

I am told quite frequently that an organisation is not "mature" enough for machine learning. By this, managers usually mean one of the following things items are not at a level deemed adequate: This falls back into the very common trap with managers ...

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Guido Tapia

April 13, 2018

Diminishing Returns in Machine Learning Projects

Any machine learning practitioner will tell you that there is a certain point in time where trying to eke out more performance/accuracy from a project seems like more effort than its worth. At PicNet we always suggest customers run a 4-6-week proof o ...

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Guido Tapia

May 5, 2019

PyTorch Implementation of "Unsupervised learning by competing hidden units" MNIST classifier

I recently watched this lecture by Dmitry Krotov and found it very interesting so I thought it would make a good paper to try to reproduce. My original thoughts were that this could potentially solve the adversarial vulnerability inherent in most mod ...

in machine-learning software-engineering