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 …
Get the source code and data on Github
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 …
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 …
OMG I can't believe I missed this competition. It's exactly in line with my whaleshark identification project.
https://www.kaggle.com/c/humpback-whale-identification
Here's a baby humpback whale that swam up to the boat a few weeks ago. In the second photo you can see it popped it's head up …