Patterns, predictions, and actions: A story about machine learning
Patterns, predictions, and actions: A story about machine learning
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模式、预测和行动：关于机器学习的故事
DOI：
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发表时间：
2021
期刊：
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通讯作者：
B. Recht
中科院分区：
文献类型：
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作者：
Moritz Hardt;B. Recht
这本关于机器学习的研究生教科书讲述了数据中的模式如何支持预测和相应的行动。从决策制定的基础开始，我们涵盖了表示、优化和泛化作为监督学习的组成部分。关于数据集作为基准的一章考察了它们的历史和科学基础。自成一体的因果关系介绍，因果推理的实践，顺序决策和强化学习，为读者配备了关于行为及其后果的推理的概念和工具。全文从头到尾都在讨论历史背景和社会影响。我们邀请来自各种背景的读者；具备一些概率、微积分和线性代数的经验就足够了。
This graduate textbook on machine learning tells a story of how patterns in data support predictions and consequential actions. Starting with the foundations of decision making, we cover representation, optimization, and generalization as the constituents of supervised learning. A chapter on datasets as benchmarks examines their histories and scientific bases. Self-contained introductions to causality, the practice of causal inference, sequential decision making, and reinforcement learning equip the reader with concepts and tools to reason about actions and their consequences. Throughout, the text discusses historical context and societal impact. We invite readers from all backgrounds; some experience with probability, calculus, and linear algebra suffices.