[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fT18cbqODZzGKLLa5tdYgrZlTvulW8xX59rBKeJRqTt4":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":13,"related":14,"source":25,"type":78},[],"2025-05-19 08:06:57",1069534660,[8,9,10,11],"大语言模型是基于深度学习的自然语言处理技术","大语言模型的应用仅限于文本生成","大语言模型可以用于机器翻译、对话系统等多个领域","大语言模型能够理解和生成多种语言的文本",{},"以下关于大语言模型(LLM)的说法,哪些是正确的?( )",[15,27,36,41,50,60,65,70,75,79],{"answer":16,"createTime":17,"id":18,"options":19,"question":24,"source":25,"type":26},[],"2025-05-19 08:06:56",1069534621,[20,21,22,23],"print(torch.version)","print(torch.cuda.is_available())","import torch","conda install pytorch","验证PyTorch是否支持GPU的命令是?( )","v2",0,{"answer":28,"createTime":29,"id":30,"options":31,"question":34,"source":25,"type":35},[],"2025-05-19 08:06:58",1069534623,[32,33],"对","错","LSTM只使用输入门和输出门,而遗忘门并不是其必要组成部分.( )",3,{"answer":37,"createTime":29,"id":38,"options":39,"question":40,"source":25,"type":35},[],1069534627,[32,33],"在Jaccard相似度计算中,值越大,相似度越小.( )",{"answer":42,"createTime":17,"id":43,"options":44,"question":49,"source":25,"type":26},[],1069534631,[45,46,47,48],"用户需求能够帮助设计团队更好地理解市场趋势","用户需求直接影响产品功能的设计和性能指标的制定","用户需求是产品营销策略的基础","用户需求能够提高公司内部沟通的效率","在进行产品设计时,明确用户需求是非常重要的一步.以下哪项最能体现用户需求对功能与性能指标设计的重要性?( )",{"answer":51,"createTime":52,"id":53,"options":54,"question":59,"source":25,"type":26},[],"2025-05-19 08:06:55",1069534636,[55,56,57,58],"数据清洗","特征工程","数据集划分","数据可视化","在数据预处理过程中,以下哪一项是确保数据适用于LSTM模型训练的关键步骤?( )",{"answer":61,"createTime":5,"id":62,"options":63,"question":64,"source":25,"type":35},[],1069534645,[32,33],"卷积神经网络(CNN)中的卷积层主要负责特征提取,通过对输入数据进行卷积操作以获取特征图.池化层则用于降低特征图的维度,同时保留重要特征.全连接层的作用是将提取到的特征转换为最终的输出结果.根据这些描述,以下说法正确吗:在卷积神经网络中,池化层并不参与特征提取,而是纯粹用于降低数据维度,因此可以被忽略.( )",{"answer":66,"createTime":29,"id":67,"options":68,"question":69,"source":25,"type":35},[],1069534654,[32,33],"线性回归假设自变量与因变量之间存在线性关系,而非线性回归则用于处理非线性关系.因此,对于任一回归问题,采用非线性回归都比线性回归都有更好的效果.( )",{"answer":71,"createTime":29,"id":72,"options":73,"question":74,"source":25,"type":35},[],1069534658,[32,33],"在人工智能开发中,Pandas主要用于数据的清洗和处理,而NumPy则用于高效的数值计算,Matplotlib则用于数据可视化.因此,以下说法是正确的:Pandas、NumPy和Matplotlib都是人工智能开发中不可或缺的工具库.( )",{"answer":76,"createTime":5,"id":6,"options":77,"question":13,"source":25,"type":78},[],[8,9,10,11],1,{"answer":80,"createTime":29,"id":81,"options":82,"question":83,"source":25,"type":35},[],1069534662,[32,33],"在手写数字识别的基本流程中,首先需要进行数据加载,然后选择合适的模型,最后再进行评估与优化.因此,数据加载、模型选择以及评估与优化是手写数字识别的三个重要步骤,其他步骤并不重要.( )"]