| #2 |  Veridical Data Science: The Practice of Responsible Data Analysis and Decision Making
| 5 |
| #3 |  Strong Towns
| 4.04 |
| #4 |  Escaping the Housing Trap: The Strong Towns Response to the Housing Crisis
| 0 |
| #5 |  Probability Theory: The Logic of Science
| 0 |
| #6 |  Interpretable Machine Learning Interpretable Machine Learning: A Guide For Making Black Box Models Explainable
| 5 |
| #7 |  Modeling Mindsets: The Many Cultures Of Learning From Data
| 4 |
| #8 |  Supervised Machine Learning for Science: How to stop worrying and love your black box
| 4 |
| #9 |  An Introduction to Optimization on Smooth Manifolds
| 0 |
| #10 |  Geometric Deep Learning Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
| 4 |
| #11 |  Statistical Rethinking: A Bayesian Course with Examples in R and Stan
| 0 |
| #12 |  Forming Humanity: Redeeming the German Bildung Tradition
| 5 |
| #13 |  Structure and Interpretation of Computer Programs
| 4.18 |
| #14 | Category Theory for Programmers Category Theory for Programmers
| 3 |
| #15 |  Regression and Other Stories
| 0 |
| #16 |  Bayesian Data Analysis
| 0 |
| #17 |  Causal Inference and American Political Development: New Frontiers | 4 |
| #18 |  Bernoulli's Fallacy: Statistical Illogic and the Crisis of Modern Science
| 4 |
| #19 |  Public Policy Analysis Public Policy Analysis: An Integrated Approach
| 5 |
| #20 |  Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist
| 3.97 |
| #21 |  Critical Data Studies: An A to Z Guide to Concepts and Methods
| 0 |
| #22 |  Bullshit Jobs: A Theory
| 3.9 |
| #23 |  Hegel’s Moral Corporation
| 4 |
