— Insight —
A lot of companies make the mistake of looking for unicorns. Here's a practical approach for finding a better alternative.
— Sponsored Link —
Bias comes in a variety of forms, all of them potentially damaging to the efficacy of your ML algorithm. Our Chief Data Scientist specializes in training data bias, the source of most headlines about AI failures. Our overview on the subject – Four Types of AI Bias – offers guidelines for detecting and mitigating bias.
— Tools and Techniques —
It's common to acquire technical debt but there's a difference between debt that's healthy and debt that results from poor development practices. This post by Gordon Shotwell walks through what you should be doing and how to get back on track if your projects are already deep in debt.
Real numbers, data science and chaos: How to fit any dataset with a single parameter!
When StitchFix needed a lot more data than it had, its data science team got creative. Here's how their "Style Shuffle" game has generated more than a billion product ratings while StitchFix learns what its customers are likely to buy.
Prophet is a time series forecasting tool that was developed at Facebook and released as an open-source project. This Twitter thread by Sean J. Taylor is a fantastic overview of what it does and how it works.
On May 15th, 1pm ET, Sr. Data Scientist Kerstin Frailey will discuss the challenges of strategic planning for data science and how to overcome them. It's a workshop designed for business leaders, data science managers, and decision makers who want to build effective AI and data science capabilities for their organization.
— Resources —
Skills like coding, unit testing and continuous integration are increasingly important for data science work. So for developers who already have those skills, "data science" is creating interesting new career possibilities. Here's a great overview for developers that are thinking about a move.
— Data Viz —
I love this project. Simple, beautiful and effective.