Featuring Data

[#15] AI Ethics and Fairness

"What is Fair, Anyways?"

Apr 6, 2021 • 

Dan Capellupo

March 2021

[#14] Occam's Razor

Sometimes the simplest answer is the best answer

Mar 23, 2021 • 

Dan Capellupo

[#13] The Drive to Become Data-Driven

As companies continue to move towards becoming more data-driven, what are the opportunities and challenges for data professionals?

Mar 9, 2021 • 

Dan Capellupo

February 2021

[#12] Deep Dive into Clustering (Part 2)

k-Means and HDBSCAN: a detailed comparison

Feb 25, 2021 • 

Dan Capellupo

[#11] Deep Dive into Clustering (Part 1)

The k-Means algorithm and choosing the number of clusters

Feb 10, 2021 • 

Dan Capellupo

1

January 2021

[#10] Rules and ML

Does machine learning replace rules or can they work together?

Jan 26, 2021 • 

Dan Capellupo

[#9] Crowdsourcing Data Science

How much do subjective analytical choices influence one's results?

Jan 19, 2021 • 

Dan Capellupo

[#8] Data Science, in General

How should companies prioritize hiring generalists over specialists, and how does that affect your job search?

Jan 12, 2021 • 

Dan Capellupo

[#7] All Roads Lead to Data Science

There are many unique paths to becoming a data scientist

Jan 5, 2021 • 

Dan Capellupo

December 2020

[#6] The Missing Piece of the Most Popular Online Data Science Courses

Explainability and ethics in machine learning and AI should be introduced to aspiring data scientists from the beginning

Dec 22, 2020 • 

Dan Capellupo

[#5] The Top Statistics Ideas of the Last 50 Years

The most important developments in statistics since 1970 and their connection to modern data science

Dec 15, 2020 • 

Dan Capellupo

[#4] Machine Learning versus Statistics

How do machine learning practitioners differ from statisticians in their approach to a problem?

Dec 8, 2020 • 

Dan Capellupo