{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","title":"人工智能与大数据技术导论","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787302517986","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","id":"cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","uuid":"cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","title":"人工智能与大数据技术导论","normalized_title":"人工智能与大数据技术导论","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787302517986","isbns":["9787302517986"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":490,"navigation_url":"https://workshop.closeclaw.top/ai/book/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","title_url":"https://workshop.closeclaw.top/ai/title/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E4%B8%8E%E5%A4%A7%E6%95%B0%E6%8D%AE%E6%8A%80%E6%9C%AF%E5%AF%BC%E8%AE%BA","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","page_url":"https://workshop.closeclaw.top/api/ai/books/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71/page","search_url":"https://workshop.closeclaw.top/api/ai/books/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71/search"},"page":{"printed_page":371,"pdf_page":387,"physical_index":387,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"33b9f950bfdee3624ca7f4345fe8e452d9a930b6343df83214f959e06a8a7f8c"},"chapter":"第10章","content":"从上面的几个例子中，我们获得了比原来的线性模型更好且具有嵌套的DNN模型，但线性模型也相当不错，而且训练速度快得多。线性模型的训练速度之所以更快，是因为没有太多要更新的参数或要反向传播的层。在有些应用中，线性模型的速度可能非常关键，或者从质量的角度来看，线性模型可能完全够用。在其他领域，DNN提供的额外模型的复杂性和能力可能更重要。另外，在训练LinearClassifier或DNNClassifier时，需要根据实际情况使用稀疏列。TF提供了两个选项：embedding column 或 indicator\\_column。在训练 LinearClassifier 时，系统在后台使用了embeddingcolumn。在训练DNNClassifier时，我们必须明确地选择embedding\\_column 或 indicator\\_column。\n\n第10章 神经网络\n\n371","previous_page":370,"next_page":null}