By Cody Marie Wild – 15 min read
I’m going to tell a story: one you’ve almost certainly heard before, but with a different emphasis than you’re used to.
Why Model Explainability is The Next Data Science Superpower
By Dan Becker – 4 min read
I’ve interviewed many data scientists in the last 10 years, and model explainability techniques are my favorite topic to distinguish the very best data scientists from the average.
How Transformers Work
By Giuliano Giacaglia – 14 min read
Transformers are a type of neural network architecture that have been gaining popularity. Transformers were recently used by OpenAI in their language models, and also used recently by DeepMind for AlphaStar – their program to defeat a top professional Starcraft player.
From ‘R vs Python’ to ‘R and Python’
By Parul Pandey – 7 min read
Leveraging the best of both ‘Python and R’ in a single project.
Building support for pollution-free cities: an Open Data workflow
By Nick Jones – 6 min read
Air pollution is one of the great killers of our age, causing 6.4 million deaths in 2015 according to a Lancet study – compared with 0.7 million from malaria. How can we drive more action to tackle it? In this post, we’ll walk through the steps to build a data-driven advocacy tool using Python code.
Gaussian Mixture Modelling (GMM)
By Daniel Foley – 11 min read
Making Sense of Text Data using Unsupervised Learning
Jupyter Superpower – Interactive Visualization Combo with Python
By Nok – 5 min read
altair is an interactive visualization library. It offers a more consistent API. This is how the authors describe the library.
Building an Employee Churn Model in Python to Develop a Strategic Retention Plan
By Hamza Bendemra – 13 min read
Employee turn-over (also known as "employee churn") is a costly problem for companies. The true cost of replacing an employee can often be quite large.
10 Python Pandas tricks that make your work more efficient
By Shiu-Tang Li – 5 min read
Some commands you may know already but may not know they can be used this way.