Probabilistic Graphical Models: Principles and Techniques by Daphne Koller and Nir Friedman vs Feature Engineering for Machine Learning by Alice Zheng and Amanda Casari: Which Is Better?

Quick Verdict

Both Probabilistic Graphical Models: Principles and Techniques by Daphne Koller and Nir Friedman and Feature Engineering for Machine Learning by Alice Zheng and Amanda Casari are excellent tools in their category. Feature Engineering for Machine Learning by Alice Zheng and Amanda Casari edges ahead with a 5.0 rating compared to Probabilistic Graphical Models: Principles and Techniques by Daphne Koller and Nir Friedman's 3.7. Your choice depends on your specific needs, team size, and budget.