* Fooled By Randomness (NN Taleb): Taleb is a complicated personality, but this book gave me a heuristic for thinking about long-tails and uncertain events that I could never have derived myself from a probability textbook.
* Designing Data Intensive Applications (M Kleppmann): Provided a first-principles approach for thinking about the design of modern large-scale data infrastructure. It's not just about assembling different technologies -- there are principles behind how data moves and transforms that transcend current technology, and DDIA is an articulation of those principles. After reading this, I began to notice general patterns in data infrastructure, which helped me quickly grasp how new technologies worked. (most are variations on the same principles)
* Introduction to Statistical Learning (James et al) and Applied Predictive Modeling (Kuhn et al). These two books gave me a grand sweep of predictive modeling methods pre-deep learning, methods which continue to be useful and applicable to a wider variety of problem contexts than AI/Deep Learning. (neural networks aren't appropriate for huge classes of problems)
* High Output Management (A Grove): oft-recommended book by former Intel CEO Andy Grove on how middle management in large corporations actually works, from promotions to meetings (as a unit of work). This was my guide to interpreting my experiences when I joined a large corporation and boy was it accurate. It gave me a language and a framework for thinking about what was happening around me. I heard this was 1 of 2 books Tobi Luetke read to understand management when he went from being a technical person to CEO of Shopify. (the other book being Cialdini's Influence). Hard Things about Hard Things (B Horowitz) is a different take that is also worth a read to understand the hidden--but intentional--managerial design of a modern tech company. These some of the very few books written by practitioners--rather than management gurus--that I've found to track pretty closely with my own real life experiences.
I have a small company that sells 3D printed jewelry (https://lulimjewelry.com) and I use blender to automatically generate STL files ready for printing with my customers designs engraved on them.
Their scripting support is top notch. Virtually everything you can do in the GUI is accessible with the scripting library. You can even pop open a window that shows the equivalent python commands to actions you are doing in the GUI. They have a nice integrated editor for writing/debugging, and when you are all done you can run it headless from the command line.
I have blender running in a docker container on google cloud run that spits out STL files, which is awesome.
* Designing Data Intensive Applications (M Kleppmann): Provided a first-principles approach for thinking about the design of modern large-scale data infrastructure. It's not just about assembling different technologies -- there are principles behind how data moves and transforms that transcend current technology, and DDIA is an articulation of those principles. After reading this, I began to notice general patterns in data infrastructure, which helped me quickly grasp how new technologies worked. (most are variations on the same principles)
* Introduction to Statistical Learning (James et al) and Applied Predictive Modeling (Kuhn et al). These two books gave me a grand sweep of predictive modeling methods pre-deep learning, methods which continue to be useful and applicable to a wider variety of problem contexts than AI/Deep Learning. (neural networks aren't appropriate for huge classes of problems)
* High Output Management (A Grove): oft-recommended book by former Intel CEO Andy Grove on how middle management in large corporations actually works, from promotions to meetings (as a unit of work). This was my guide to interpreting my experiences when I joined a large corporation and boy was it accurate. It gave me a language and a framework for thinking about what was happening around me. I heard this was 1 of 2 books Tobi Luetke read to understand management when he went from being a technical person to CEO of Shopify. (the other book being Cialdini's Influence). Hard Things about Hard Things (B Horowitz) is a different take that is also worth a read to understand the hidden--but intentional--managerial design of a modern tech company. These some of the very few books written by practitioners--rather than management gurus--that I've found to track pretty closely with my own real life experiences.