DataScienceHorizons2024掌握生成式AI与提示工程数据科学家的实用指南英文版42页

MasteringGenerativeAIandPromptEngineering:APracticalGuideforDataScientistsAstheAI-driveneconomycontinuestoevolveandexpand,theroleofpromptengineeringwillbecomeincreasinglysignificantandtransformativeacrossdiversesectorsanddomains.ContentsIntroductionChapter1:UnderstandingGenerativeAI1.1.EvolutionofAI:Fromrule-basedtogenerativemodels1.2.KeygenerativeAImodels:RNNs,LSTMs,GPT,andmore1.3.PopularusecasesforgenerativeAIChapter2:IntroductiontoPromptEngineering2.1.Whatispromptengineeringandwhyitmatters2.2.Prompttypes:explicit,implicit,andcreativeprompts2.3.TheroleofpromptsinguidingAImodelsChapter3:DesigningE�ectivePrompts3.1.UnderstandingyourAImodel:capabilitiesandlimitations3.2.Craftingclearandconciseprompts3.3.Usingtokens,temperature,andotherparameters3.4.Iterativepromptdesign:testingandrefiningChapter4:AdvancedPromptEngineeringTechniques4.1.Conditionalpromptsforcontext-sensitiveAI4.2.Multi-steppromptsforcomplextasks4.3.LeveragingtransferlearningforpromptengineeringChapter5:EthicalConsideration