gluonbook.md

# `gluonbook`包索引


函数、类等名称：定义所在章节

* `bbox_to_rect`：[物体检测和边界框](../chapter_computer-vision/bounding-box.md)
* `Benchmark`：[异步计算](../chapter_computational-performance/async-computation.md)
* `corr2d`：[二维卷积层](../chapter_convolutional-neural-networks/conv-layer.md)
* `count_tokens`：[文本情感分类：使用循环神经网络](../chapter_natural-language-processing/sentiment-analysis-rnn.md)
* `data_iter`：[线性回归的从零开始实现](../chapter_deep-learning-basics/linear-regression-scratch.md)
* `data_iter_consecutive`：[语言模型数据集（周杰伦专辑歌词）](../chapter_recurrent-neural-networks/lang-model-dataset.md)
* `data_iter_random`：[语言模型数据集（周杰伦专辑歌词）](../chapter_recurrent-neural-networks/lang-model-dataset.md)
* `download_imdb`：[文本情感分类：使用循环神经网络](../chapter_natural-language-processing/sentiment-analysis-rnn.md)
* `download_voc_pascal`：[语义分割和数据集](../chapter_computer-vision/semantic-segmentation-and-dataset.md)
* `evaluate_accuracy`：[图像增广](../chapter_computer-vision/image-augmentation.md)
* `get_data_ch7`：[小批量随机梯度下降](../chapter_optimization/minibatch-sgd.md)
* `get_fashion_mnist_labels`：[图像分类数据集（Fashion-MNIST）](../chapter_deep-learning-basics/fashion-mnist.md)
* `get_tokenized_imdb`：[文本情感分类：使用循环神经网络](../chapter_natural-language-processing/sentiment-analysis-rnn.md)
* `get_vocab_imdb`：[文本情感分类：使用循环神经网络](../chapter_natural-language-processing/sentiment-analysis-rnn.md)
* `grad_clipping`：[循环神经网络的从零开始实现](../chapter_recurrent-neural-networks/rnn-scratch.md)
* `linreg`：[线性回归的从零开始实现](../chapter_deep-learning-basics/linear-regression-scratch.md)
* `load_data_fashion_mnist`：[深度卷积神经网络（AlexNet）](../chapter_convolutional-neural-networks/alexnet.md)
* `load_data_jay_lyrics`：[语言模型数据集（周杰伦专辑歌词）](../chapter_recurrent-neural-networks/lang-model-dataset.md)
* `load_data_pikachu`：[物体检测数据集（皮卡丘）](../chapter_computer-vision/object-detection-dataset.md)
* `mkdir_if_not_exist`：[实战Kaggle比赛：图像分类（CIFAR-10）](../chapter_computer-vision/kaggle-gluon-cifar10.md)
* `plt`：[线性回归的从零开始实现](../chapter_deep-learning-basics/linear-regression-scratch.md)
* `predict_rnn`：[循环神经网络的从零开始实现](../chapter_recurrent-neural-networks/rnn-scratch.md)
* `predict_rnn_gluon`：[循环神经网络的简洁实现](../chapter_recurrent-neural-networks/rnn-gluon.md)
* `predict_sentiment`：[文本情感分类：使用循环神经网络](../chapter_natural-language-processing/sentiment-analysis-rnn.md)
* `preprocess_imdb`：[文本情感分类：使用循环神经网络](../chapter_natural-language-processing/sentiment-analysis-rnn.md)
* `read_imdb`：[文本情感分类：使用循环神经网络](../chapter_natural-language-processing/sentiment-analysis-rnn.md)
* `read_voc_images`：[语义分割和数据集](../chapter_computer-vision/semantic-segmentation-and-dataset.md)
* `Residual`：[残差网络（ResNet）](../chapter_convolutional-neural-networks/resnet.md)
* `resnet18`：[多GPU计算的简洁实现](../chapter_computational-performance/multiple-gpus-gluon.md)
* `RNNModel`：[循环神经网络的简洁实现](../chapter_recurrent-neural-networks/rnn-gluon.md)
* `semilogy`：[模型选择、欠拟合和过拟合](../chapter_deep-learning-basics/underfit-overfit.md)
* `set_figsize`：[线性回归的从零开始实现](../chapter_deep-learning-basics/linear-regression-scratch.md)
* `sgd`：[线性回归的从零开始实现](../chapter_deep-learning-basics/linear-regression-scratch.md)
* `show_bboxes`：[锚框](../chapter_computer-vision/anchor.md)
* `show_fashion_mnist`：[图像分类数据集（Fashion-MNIST）](../chapter_deep-learning-basics/fashion-mnist.md)
* `show_images`：[图像增广](../chapter_computer-vision/image-augmentation.md)
* `show_trace_2d`：[梯度下降和随机梯度下降](../chapter_optimization/gd-sgd.md)
* `squared_loss`：[线性回归的从零开始实现](../chapter_deep-learning-basics/linear-regression-scratch.md)
* `to_onehot`：[循环神经网络的从零开始实现](../chapter_recurrent-neural-networks/rnn-scratch.md)
* `train`：[图像增广](../chapter_computer-vision/image-augmentation.md)
* `train_2d`：[梯度下降和随机梯度下降](../chapter_optimization/gd-sgd.md)
* `train_and_predict_rnn`：[循环神经网络的从零开始实现](../chapter_recurrent-neural-networks/rnn-scratch.md)
* `train_and_predict_rnn_gluon `：[循环神经网络的简洁实现](../chapter_recurrent-neural-networks/rnn-gluon.md)
* `train_ch3`：[Softmax回归的从零开始实现](../chapter_deep-learning-basics/softmax-regression-scratch.md)
* `train_ch5`：[卷积神经网络（LeNet）](../chapter_convolutional-neural-networks/lenet.md)
* `train_ch7`：[小批量随机梯度下降](../chapter_optimization/minibatch-sgd.md)
* `train_gluon_ch7`：[小批量随机梯度下降](../chapter_optimization/minibatch-sgd.md)
* `try_all_gpus`：[图像增广](../chapter_computer-vision/image-augmentation.md)
* `try_gpu`：[卷积神经网络（LeNet）](../chapter_convolutional-neural-networks/lenet.md)
* `use_svg_display`：[线性回归的从零开始实现](../chapter_deep-learning-basics/linear-regression-scratch.md)
* `VOC_CLASSES`：[语义分割和数据集](../chapter_computer-vision/semantic-segmentation-and-dataset.md)
* `VOC_COLORMAP`：[语义分割和数据集](../chapter_computer-vision/semantic-segmentation-and-dataset.md)
* `voc_label_indices`：[语义分割和数据集](../chapter_computer-vision/semantic-segmentation-and-dataset.md)
* `voc_rand_crop`：[语义分割和数据集](../chapter_computer-vision/semantic-segmentation-and-dataset.md)
* `VOCSegDataset`：[语义分割和数据集](../chapter_computer-vision/semantic-segmentation-and-dataset.md)