整体进度（校对）

| 章节 | 贡献者 | 进度 |
| --- | --- | --- |
| 深度学习与 Keras | - | - |
| [Keras 中神经网络模型的 5 步生命周期](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/5-step-life-cycle-neural-network-models-keras.md) | @ElmaDavies | 100% |
| [在 Python 迷你课程中应用深度学习](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/applied-deep-learning-in-python-mini-course.md) |@ElmaDavies |100% |
| [Keras 深度学习库的二元分类教程](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/binary-classification-tutorial-with-the-keras-deep-learning-library.md) | @ElmaDavies |100% |
| [如何用 Keras 构建多层感知器神经网络模型](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/build-multi-layer-perceptron-neural-network-models-keras.md) | @Lnssssss | 100% |
| [如何在 Keras 中检查深度学习模型](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/check-point-deep-learning-models-keras.md) |@ElmaDavies | 100% |
| [10 个用于 Amazon Web Services 深度学习的命令行秘籍](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/command-line-recipes-deep-learning-amazon-web-services.md) | @Lnssssss | 100% |
| [机器学习卷积神经网络的速成课程](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/crash-course-convolutional-neural-networks.md) | @ElmaDavies | 100% |
| [如何在 Python 中使用 Keras 进行深度学习的度量](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/custom-metrics-deep-learning-keras-python.md) | @Lnssssss | 100% |
| [深度学习书籍](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/deep-learning-books.md) | @Lnssssss |100% |
| [深度学习课程](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/deep-learning-courses.md) |@ElmaDavies | 100%|
| [你所知道的深度学习是一种谎言](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/deep-learning-for-developers.md) | @Lnssssss | 100% |
| [如何设置 Amazon AWS EC2 GPU 以训练 Keras 深度学习模型（分步）](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/develop-evaluate-large-deep-learning-models-keras-amazon-web-services.md) | @ElmaDavies |100% |
| [神经网络中批量和迭代之间的区别是什么？](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/difference-between-a-batch-and-an-epoch.md) | @Lnssssss | 100% |
| [在 Keras 展示深度学习模型训练历史](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/display-deep-learning-model-training-history-in-keras.md) |@ElmaDavies | 100% |
| [基于 Keras 的深度学习模型中的dropout正则化](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/dropout-regularization-deep-learning-models-keras.md) | @Lnssssss | 100% |
| [评估 Keras 中深度学习模型的性能](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/evaluate-performance-deep-learning-models-keras.md) | @ElmaDavies | 100%|
| [评估深度学习模型的技巧](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/evaluate-skill-deep-learning-models.md) |@ElmaDavies | 100% |
| [小批量梯度下降的简要介绍以及如何配置批量大小](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/gentle-introduction-mini-batch-gradient-descent-configure-batch-size.md) | @Lnssssss | |
| [在 Keras 中获得深度学习帮助的 9 种方法](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/get-help-with-keras.md) | @ElmaDavies | 100% |
| [如何使用 Keras 在 Python 中网格搜索深度学习模型的超参数](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/grid-search-hyperparameters-deep-learning-models-python-keras.md) |@ElmaDavies | 100% |
| [用 Keras 在 Python 中使用卷积神经网络进行手写数字识别](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/handwritten-digit-recognition-using-convolutional-neural-networks-python-keras.md) | @ElmaDavies |100% |
| [如何用 Keras 进行预测](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/how-to-make-classification-and-regression-predictions-for-deep-learning-models-in-keras.md) | @ElmaDavies | 100% |
| [用 Keras 进行深度学习的图像增强](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/image-augmentation-deep-learning-keras.md) |@ElmaDavies |100% |
| [8 个深度学习的鼓舞人心的应用](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/inspirational-applications-deep-learning.md) |@ElmaDavies |100% |
| [Python 深度学习库 Keras 简介](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/introduction-python-deep-learning-library-keras.md) | @AndrewChung-GitHub | 100% |
| [Python 深度学习库 TensorFlow 简介](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/introduction-python-deep-learning-library-tensorflow.md) | @zhaop33 | 100% |
| [Python 深度学习库 Theano 简介](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/introduction-python-deep-learning-library-theano.md) | | |
| [如何使用 Keras 函数式 API 进行深度学习](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/keras-functional-api-deep-learning.md) | @AndrewChung-GitHub | |
| [Keras 深度学习库的多类分类教程](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/multi-class-classification-tutorial-keras-deep-learning-library.md) | | |
| [多层感知器神经网络速成课程](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/neural-networks-crash-course.md) | | |
| [基于卷积神经网络的 Keras 深度学习库中的目标识别](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/object-recognition-convolutional-neural-networks-keras-deep-learning-library.md) | | |
| [流行的深度学习库](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/popular-deep-learning-libraries.md) | | |
| [用深度学习预测电影评论的情感](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/predict-sentiment-movie-reviews-using-deep-learning.md) | | |
| [Python 中的 Keras 深度学习库的回归教程](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/regression-tutorial-keras-deep-learning-library-python.md) | | |
| [如何使用 Keras 获得可重现的结果](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/reproducible-results-neural-networks-keras.md) | @AndrewChung-GitHub | |
| [如何在 Linux 服务器上运行深度学习实验](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/run-deep-learning-experiments-linux-server.md) | | |
| [保存并加载您的 Keras 深度学习模型](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/save-load-keras-deep-learning-models.md) | @AndrewChung-GitHub | |
| [用 Keras 逐步开发 Python 中的第一个神经网络](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/tutorial-first-neural-network-python-keras.md) | @AndrewChung-GitHub | |
| [用 Keras 理解 Python 中的有状态 LSTM 循环神经网络](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/understanding-stateful-lstm-recurrent-neural-networks-python-keras.md) | @AndrewChung-GitHub | |
| [在 Python 中使用 Keras 深度学习模型和 Scikit-Learn](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/use-keras-deep-learning-models-scikit-learn-python.md) | @AndrewChung-GitHub | |
| [如何使用预训练的 VGG 模型对照片中的物体进行分类](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/use-pre-trained-vgg-model-classify-objects-photographs.md) | | |
| [在 Python 和 Keras 中对深度学习模型使用学习率调度](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/using-learning-rate-schedules-deep-learning-models-python-keras.md) | | |
| [如何在 Keras 中可视化深度学习神经网络模型](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/visualize-deep-learning-neural-network-model-keras.md) | | |
| [什么是深度学习？](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/what-is-deep-learning.md) | | |
| [何时使用 MLP，CNN 和 RNN 神经网络](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/when-to-use-mlp-cnn-and-rnn-neural-networks.md) | | |
| [为什么用随机权重初始化神经网络？](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/dl-keras/why-initialize-a-neural-network-with-random-weights.md) | | |
| XGBoost | - | - |
| [通过在 Python 中使用 XGBoost 提前停止来避免过度拟合](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/avoid-overfitting-by-early-stopping-with-xgboost-in-python.md) | @tabeworks | 100% |
| [如何在 Python 中调优 XGBoost 的多线程支持](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/best-tune-multithreading-support-xgboost-python.md) |@tabeworks | 100% |
| [如何配置梯度提升算法](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/configure-gradient-boosting-algorithm.md) | | |
| [在 Python 中使用 XGBoost 进行梯度提升的数据准备](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/data-preparation-gradient-boosting-xgboost-python.md) | | |
| [如何使用 scikit-learn 在 Python 中开发您的第一个 XGBoost 模型](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/develop-first-xgboost-model-python-scikit-learn.md) | @tabeworks | |
| [如何在 Python 中使用 XGBoost 评估梯度提升模型](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/evaluate-gradient-boosting-models-xgboost-python.md) | | |
| [在 Python 中使用 XGBoost 的特征重要性和特征选择](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/feature-importance-and-feature-selection-with-xgboost-in-python.md) | | |
| [浅谈机器学习的梯度提升算法](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/gentle-introduction-gradient-boosting-algorithm-machine-learning.md) | | |
| [应用机器学习的 XGBoost 简介](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/gentle-introduction-xgboost-applied-machine-learnin.md) | @tabeworks | 100% |
| [如何在 macOS 上为 Python 安装 XGBoost](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/install-xgboost-python-macos.md) | | |
| [如何在 Python 中使用 XGBoost 保存梯度提升模型](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/save-gradient-boosting-models-xgboost-python.md) | | |
| [从梯度提升开始，比较 165 个数据集上的 13 种算法](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/start-with-gradient-boosting.md) | | |
| [在 Python 中使用 XGBoost 和 scikit-learn 进行随机梯度提升](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/stochastic-gradient-boosting-xgboost-scikit-learn-python.md) | | |
| [如何使用 Amazon Web Services 在云中训练 XGBoost 模型](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/train-xgboost-models-cloud-amazon-web-services.md) | | |
| [在 Python 中使用 XGBoost 调整梯度提升的学习率](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/tune-learning-rate-for-gradient-boosting-with-xgboost-in-python.md) | | |
| [如何在 Python 中使用 XGBoost 调整决策树的数量和大小](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/tune-number-size-decision-trees-xgboost-python.md) | | |
| [如何在 Python 中使用 XGBoost 可视化梯度提升决策树](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/visualize-gradient-boosting-decision-trees-xgboost-python.md) | | |
| [在 Python 中开始使用 XGBoost 的 7 步迷你课程](https://github.com/apachecn/ml-mastery-zh/blob/master/docs/xgboost/xgboost-python-mini-course.md) | | |