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[#15] AI Ethics and Fairness
"What is Fair, Anyways?"
Dan Capellupo
Apr 6
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[#14] Occam's Razor
Sometimes the simplest answer is the best answer
Dan Capellupo
Mar 23
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[#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?
Dan Capellupo
Mar 9
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[#12] Deep Dive into Clustering (Part 2)
k-Means and HDBSCAN: a detailed comparison
Dan Capellupo
Feb 25
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[#11] Deep Dive into Clustering (Part 1)
The k-Means algorithm and choosing the number of clusters
Dan Capellupo
Feb 10
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[#10] Rules and ML
Does machine learning replace rules or can they work together?
Dan Capellupo
Jan 26
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[#9] Crowdsourcing Data Science
How much do subjective analytical choices influence one's results?
Dan Capellupo
Jan 19
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[#8] Data Science, in General
How should companies prioritize hiring generalists over specialists, and how does that affect your job search?
Dan Capellupo
Jan 12
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[#7] All Roads Lead to Data Science
There are many unique paths to becoming a data scientist
Dan Capellupo
Jan 5
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[#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
Dan Capellupo
Dec 22, 2020
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[#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
Dan Capellupo
Dec 15, 2020
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[#4] Machine Learning versus Statistics
How do machine learning practitioners differ from statisticians in their approach to a problem?
Dan Capellupo
Dec 8, 2020
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