[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fAy_TAnjOP1T1iVM2CJcIGubPW6GJQaCwoPXCHPOp6K4":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":10,"question":11,"related":12,"source":23,"type":31},[],"2025-05-19 08:06:57",1069534645,[8,9],"对","错",{},"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.( )",[13,25,32,37,46,56,59,64,69,79],{"answer":14,"createTime":15,"id":16,"options":17,"question":22,"source":23,"type":24},[],"2025-05-19 08:06:56",1069534621,[18,19,20,21],"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":26,"createTime":27,"id":28,"options":29,"question":30,"source":23,"type":31},[],"2025-05-19 08:06:58",1069534623,[8,9],"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":33,"createTime":27,"id":34,"options":35,"question":36,"source":23,"type":31},[],1069534627,[8,9],"在Jaccard相似度计算中,值越大,相似度越小.( )",{"answer":38,"createTime":15,"id":39,"options":40,"question":45,"source":23,"type":24},[],1069534631,[41,42,43,44],"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":47,"createTime":48,"id":49,"options":50,"question":55,"source":23,"type":24},[],"2025-05-19 08:06:55",1069534636,[51,52,53,54],"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":57,"createTime":5,"id":6,"options":58,"question":11,"source":23,"type":31},[],[8,9],{"answer":60,"createTime":27,"id":61,"options":62,"question":63,"source":23,"type":31},[],1069534654,[8,9],"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":65,"createTime":27,"id":66,"options":67,"question":68,"source":23,"type":31},[],1069534658,[8,9],"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":70,"createTime":5,"id":71,"options":72,"question":77,"source":23,"type":78},[],1069534660,[73,74,75,76],"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?( )",1,{"answer":80,"createTime":27,"id":81,"options":82,"question":83,"source":23,"type":31},[],1069534662,[8,9],"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.( )"]