文件名称：Practical Probabilistic Programming.pdf
文件大小：6.85MB
文件格式：PDF
更新时间：2022-08-10 14:23:06
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Probabilistic programming is an exciting new field that is quickly gathering interest, moving out of the academic arena and into the world of programmers. In essence, probabilistic programming is a new way of creating models for probabilistic reasoning, which lets you predict or infer things you don’t know from observations. Probabilistic reasoning has long been one of the core approaches to machine learning, where you use a probabilistic model to describe what you know and learn from experience. Before probabilistic programming, probabilistic reasoning systems were limited to models with simple and fixed structures like Bayesian networks. Probabilistic programming sets probabilistic reasoning systems free from these shackles by providing the full power of programming languages to represent models. It’s analogous to moving from circuits to high-level programming languages