How to Use the Pandas Melt Command
Ben Cook • Posted 2020-12-22 • Last updated 2021-10-15The Pandas melt command unpivots tabular data, transforming it from wide to long format. To understand this operation, you have to know…
Object Tracking in 75 Lines of Code
Ben Cook • Posted 2020-08-01 • Last updated 2022-01-04Object tracking is pretty easy conceptually. And if you have a good detector, simple methods can be pretty effective.
Cross Entropy Loss in PyTorch
Ben Cook • Posted 2020-07-24 • Last updated 2021-10-14Cross entropy loss in PyTorch can be a little confusing. Here is a simple explanation of how it works for people who get stuck.
Pairwise Distance in NumPy
Ben Cook • Posted 2020-06-01 • Last updated 2021-10-15You can do vectorized pairwise distance calculations in NumPy (without using SciPy). This lets you extend pairwise computations to other kinds of functions.
Everything is a Pipeline
Ben Cook • Posted 2020-05-21 • Last updated 2021-03-24DAGs are everywhere in scientific computing and understanding them is key to running large computations efficiently.
Use Informative Names
Ben Cook • Posted 2020-05-18 • Last updated 2021-03-24Informative names make programming easier. Here are a few suggestions you can use to write better names in your code.
Download a YouTube Video from the Command Line with youtube-dl
Ben Cook • Posted 2020-02-15 • Last updated 2021-10-15You can use youtube-dl to download arbitrary YouTube videos from the command line. This is useful for doing machine learning on new videos.
Machine Learning Pipelines Should Be Python Packages: Transfer Learning
Ben Cook • Posted 2019-04-23 • Last updated 2021-07-08Building machine learning pipelines as well-formed Python packages simplifies transfer learning. Here’s a simple example.
Object Spread Operator for Python
Ben Cook • Posted 2019-03-17 • Last updated 2021-10-15The object spread operator is a useful pattern in JavaScript. You can do something similar in Python.
Source Code Layout for Machine Learning Pipelines
Ben Cook • Posted 2019-03-12 • Last updated 2021-10-21How you structure code in an ML pipeline makes a big difference in whether other people can easily use it. Here’s a recommendation for how to do it well.