Don’t join a team too quickly. Once you’re on a Kaggle team:
Unless you have a very good sense of what exactly your teammates are bringing to the competition, including their:
At the risk of saying, “Yeah, it’s in the docs,” this is what I did. I think the crucial thing is installed things in the proper order, so I would advise going step-by-step:
conda installed (brew install conda if not, I suppose)conda …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 could be solved (very quickly) using this code:
import …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 …
more ...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 …
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