Overfitting and Underfitting
The use of AI, machine learning, deep learning, and artificial intelligence are creating the perception that understanding the causal mechanics of a system or how the world actually works doesn’t matter because all I need to have is a marginal degree of statistical significance in my actions to make A TON of money.
Capital Flows • AI & the New Age of Learning
Businesses became flooded with dashboards, predictions, and algorithms that worked perfectly in notebooks but fell flat in real life. Executives started asking a more basic question: “What does this model mean for us?”
That’s where I began to realize that data science — in its most useful form — isn’t really about the data. It’s about decisions. And
... See moreDima Diachkov • Why Every Data Scientist Should Think Like an Economist
What is Bayesian Machine Learning?
At its heart, Bayesian Machine Learning is a statistical framework rooted in Bayes’ Theorem , a mathematical principle that describes how to update the probability of a hypothesis as new evidence becomes available.
In machine learning, this translates to modeling not just a single “best” set of parameters but a... See more
At its heart, Bayesian Machine Learning is a statistical framework rooted in Bayes’ Theorem , a mathematical principle that describes how to update the probability of a hypothesis as new evidence becomes available.
In machine learning, this translates to modeling not just a single “best” set of parameters but a... See more