Posts categorized under: ML

ML Proofs of Concept Are Hard

ML Proofs of Concept Are Hard

Cartoon showing fragile tower of dependencies

One reason why creating a business case for a Machine Learning project is difficult is that, for virtually any non-trivial task, you’re going to need, from day one of your proof-of-concept, a pretty elaborate data-preparation pipeline and, in most cases, multiple models.

For …

A Simple 3-Step AzureML Pipeline

A Simple 3-Step AzureML Pipeline (Dataprep, Training, and Evaluation)

Get the source code and data on Github

Illustration of pipeline graph

This demonstrates how you create a multistep AzureML pipeline using a series of PythonScriptStep objects.

In this case, the calculation is extremely trivial: predicting Iris species using scikit-learn's Gaussian Naive Bayes. This pipeline …

From Whalesharks To Leopard Spheres

One of my big weekend projects (for longer than I care to think) has been trying to create a pipeline for identifying individual whalesharks from photos. The project had kind of grown moribund as I repeatedly failed to get any decent level of recognition despite using what I thought was …