《工业互联网基础（双语）》课件-机器学习

机器学习工业互联网基础（双语）Machinelearning机器学习MachineLearningAmulti-disciplinaryfieldthatcombinesmultipledisciplinessuchasprobabilitytheory.Itstudieshowcomputerssimulatehumanlearningbehaviorstoacquirenewknowledge,skills,andimproveperformance多领域交叉学科，融合概率论等多学科，研究计算机模拟人类学习行为，以获取新知识、技能并改善性能。监督学习无监督学习强化学习supervisedlearningunsupervisedlearningreinforcementlearning概念学习conceptlearning监督学习superviedlearning监督学习SupervisedLearningLearnapredictivemodelfromlabeledtrainingdata.Thegoalistopredictaccurateoutputsfornewinputdata.Commonalgorithmsincludelinearregression,etc.从有标记的训练数据中学习预测模型，目标是对新输入数据预测准确输出，常见算法有线性回归等。归纳推理inductivereasoning无监督学习unsuperviedlearning无监督学习UnsupervisedLearningFindhiddenpatternsorstructuresinunlabeledtrainingdata.Thegoalistodiscovernaturalgroupingsandotherpatternsinthedata.CommonalgorithmsincludeK-Meansclustering,etc.在无标记训练数据中找隐藏模式或结构，目标是发现数据中的自然分组等规律，常见算法有K-Means聚类等。强化学习reinforcementlearning×√强化学习ReinforcementLearningTheagentinteractswiththeenvironmentandadjuststhebehaviorstrategybasedonrewardsandpunishmentstomaximizecumulativerewards.Itemphasizeslearningtheoptimalstrategythroughtrialanderroranddynamicinteraction.智能体与环境交互，根据环境奖惩调整行为策略，以最大化累积奖励，强调试错与动态交互学习最优策略。自然语言处理NaturalLanguageProcessing图像和视频处理ImageandVideoProcessing预测分析PredictiveAnalyticsQuestions人类学习能够综合多种感官和直觉进行判断，机器学习则依靠精确的数值计算，哪种方式更具优势？Humanlearningiscapableofmakingjudgmentsbyintegratingvarioussensesandintuitions,whilemachine