……Statistics》是我所知道的关于以现代眼光理解因果性问题最好的入门书。至于实际推断，其基础是单人博弈论（即决策论）。我是从 Kiefer 的《Introduction to Statistical Inference》里学到的，那本书前几章把理论梳理得非常漂亮。至少算是个切入点吧。有一些尝试通过重采样来教授统计学的有趣课程[^3]，在教学法上看起来……
…Statistics' is the best introduction I know of to issues of causality as we understand them today. For actual inference, the basis is one player game theory (aka, decision theory). I learned it from Kiefer's 'Introduction to Statistical Inference,' which sets out the theory very nicely in the first few chapters. That's a starting point at least. There are some interesting courses[^3] that try to teach statistics via resampling that seem pedagogically…
要记住《Elements of Statistical Learning》（ESL）是研究生水平的教材。如果是刚入行的新手，我绝不会抛开同一批作者写的《Introduction to Statistical Inference》去给他推 ESL。Aurélien Géron 出在 O'Reilly 的那本书很棒——《Hands-On Machine Learning with Scikit-Learn and TensorFlow》。记得买涵盖了 TensorFlow 2 的第二版。
Bear in mind Elements of Statistical Learning is a grad-level text. I would never recommend that to a beginner to the field over an Introduction to Statistical Inference, by the same authors. Geron Aurelien's Oreilly book is great - Hands-On Machine Learning with Scikit-Learn and TensorFlow. Get the second edition which covers Tensorflow 2.
……有什么书涵盖这块内容吗？朋友推荐了：* Devinderjit Sivia 和 John Skilling 的《Data Analysis: A Bayesian Tutorial》* Andrew Gelman、John B. Carlin 和 Hal S. Stern 的《Bayesian Data Analysis》* Jack C. Kiefer 和 Gary Lorden 的《Introduction to Statistical Inference》 目前我正在硬啃 Christopher M. Bishop 的《Pattern Recognition and Machine Learning》（PRML）。这些书又贵又巨耗时间，所以……
…some texts that cover this? A friend suggested: * Data Analysis: A Bayesian Tutorial by Devinderjit Sivia, John Skilling * Bayesian Data Analysis, by Andrew Gelman, John B. Carlin, Hal S. Stern * Introduction to Statistical Inference by Jack C. Kiefer, Gary Lorden Currently I am working my way through this. Pattern Recognition and Machine Learning by Christopher M. Bishop These books are expensive and very time-consuming so it…
……Statistics》是我所知道的关于以现代眼光理解因果性问题最好的入门书。至于实际推断，其基础是单人博弈论（即决策论）。我是从 Kiefer 的《Introduction to Statistical Inference》里学到的，那本书前几章把理论梳理得非常漂亮。至少算是个切入点吧。有一些尝试通过重采样来教授统计学的有趣课程[^3]，在教学法上看起来……
…Statistics' is the best introduction I know of to issues of causality as we understand them today. For actual inference, the basis is one player game theory (aka, decision theory). I learned it from Kiefer's 'Introduction to Statistical Inference,' which sets out the theory very nicely in the first few chapters. That's a starting point at least. There are some interesting courses[^3] that try to teach statistics via resampling that seem pedagogically…
要记住《Elements of Statistical Learning》（ESL）是研究生水平的教材。如果是刚入行的新手，我绝不会抛开同一批作者写的《Introduction to Statistical Inference》去给他推 ESL。Aurélien Géron 出在 O'Reilly 的那本书很棒——《Hands-On Machine Learning with Scikit-Learn and TensorFlow》。记得买涵盖了 TensorFlow 2 的第二版。
Bear in mind Elements of Statistical Learning is a grad-level text. I would never recommend that to a beginner to the field over an Introduction to Statistical Inference, by the same authors. Geron Aurelien's Oreilly book is great - Hands-On Machine Learning with Scikit-Learn and TensorFlow. Get the second edition which covers Tensorflow 2.
……有什么书涵盖这块内容吗？朋友推荐了：* Devinderjit Sivia 和 John Skilling 的《Data Analysis: A Bayesian Tutorial》* Andrew Gelman、John B. Carlin 和 Hal S. Stern 的《Bayesian Data Analysis》* Jack C. Kiefer 和 Gary Lorden 的《Introduction to Statistical Inference》 目前我正在硬啃 Christopher M. Bishop 的《Pattern Recognition and Machine Learning》（PRML）。这些书又贵又巨耗时间，所以……
…some texts that cover this? A friend suggested: * Data Analysis: A Bayesian Tutorial by Devinderjit Sivia, John Skilling * Bayesian Data Analysis, by Andrew Gelman, John B. Carlin, Hal S. Stern * Introduction to Statistical Inference by Jack C. Kiefer, Gary Lorden Currently I am working my way through this. Pattern Recognition and Machine Learning by Christopher M. Bishop These books are expensive and very time-consuming so it…