دانلود کتاب ریاضی برای برنامه نویسان – گرافیک سه بعدی، یادگیری ماشین و شبیه سازی

I started working on this book in 2017, when I was CTO of Tachyus, a company I founded that builds predictive analytics software for oil and gas companies. By that time, we had finished building our core product: a fluid-flow simulator powered by physics and machine learning, along with an optimization engine. These tools let our customers look into the future of their oil reservoirs and helped them to discover hundreds of millions of dollars of optimization opportunities. My task as CTO was to productize and scale-out this software as some of the biggest companies in the world began to use it. The challenge was that this was not only a complex software project, but the code was very mathematical. Around that time, we started hiring for a position called “scientific software engineer,” with the idea that we needed skilled professional software engineers who also had solid backgrounds in math, physics, and machine learning. In the process of searching for and hiring scientific software engineers, I realized that this combination was both rare and in high demand. Our software engineers realized this as well and were eager to hone their math skills to contribute to our specialized back-end components of our stack. With eager math learners on our team already, as well as in our hiring pipeline, I started to think about the best way to train a strong software engineer to become a formidable math user.