5 Books for Business Analysts who want to transition to a career in Machine Learning and AI.

Gabriel Botsie
Analyst’s corner
Published in
3 min readSep 24, 2023

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Image by Gabriel Botsie on Firefly

Maybe Generative AI, it’s use cases and tools has revived that interest in AI. But, how do you get started? What should you learn? What does Big Data mean? AI Pitfalls?

Here are 5 books to encourage your interest in Machine Learning and AI.

Weapons of Math Destruction. How Big Data Increases Inequality and Threatens Democracy. Cathy O’Neil

The book explores how algorithms and mathematical models can perpetuate biases, increase inequality, and threaten democracy. O’Neil draws on her experience in finance to demonstrate how opaque algorithms can have destructive impacts on people’s lives, such as in criminal sentencing and housing discrimination.

O’Neil offers concrete examples of math gone wrong and highlights the need for virtues like fairness, transparency, and auditing in algorithms.

O’Neil is a Mathematician, Data Scientist and Author. Read more of her work at mathbabe.org. Book URL

The Signal and the Noise. The Art and Science of Prediction. Nate Silver

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Gabriel Botsie
Analyst’s corner

Business Analyst, TPM writing about AI, Machine Learning, Data, Prompt Engineering & Gen AI. Here to share ideas, lessons learned. twd-advisory.com