文件名称：“深度学习Python”的Jupyter笔记本示例代码-python
文件大小：6.69MB
文件格式：ZIP
更新时间：2024-07-08 12:39:03
机器学习
Jupyter notebooks for the code samples of the book "Deep Learning with Python" “使用 Python 进行深度学习”一书的配套 Jupyter 笔记本 此存储库包含 Jupyter 笔记本，实现了使用 Python 进行深度学习（Manning Publications）一书中的代码示例。 请注意，本书原文的内容比您在这些笔记本中所能找到的要多得多，尤其是进一步的解释和图表。 在这里，我们只包含了代码示例本身和直接相关的周围注释。 这些笔记本使用 Python 3.6 和 Keras 2.0.8。 它们是在 p2.xlarge EC2 实例上生成的。 目录第 2 章：2.1：初步了解神经网络第 3 章：3.5：电影评论分类 3.6：新闻专线分类 3.7：预测房价第 4 章：4.4：欠拟合和过拟合第 5 章：5.1：卷积神经网络简介 5.2：在小数据集上使用 convnet 5.3：使用预训练的 convnet 5.4：可视化 convnet 学到了什么第 6 章：6.1：单词或字符的 One-ho
【文件预览】：
deep-learning-with-python-notebooks-master
----chapter12_part05_gans.ipynb(11KB)
----chapter11_part02_sequence-models.ipynb(13KB)
----chapter02_mathematical-building-blocks.ipynb(29KB)
----chapter08_intro-to-dl-for-computer-vision.ipynb(29KB)
----chapter12_part04_variational-autoencoders.ipynb(9KB)
----chapter14_conclusions.ipynb(13KB)
----chapter11_part04_sequence-to-sequence-learning.ipynb(18KB)
----chapter07_working-with-keras.ipynb(36KB)
----chapter09_part01_image-segmentation.ipynb(8KB)
----first_edition()
--------5.2-using-convnets-with-small-datasets.ipynb(421KB)
--------8.3-neural-style-transfer.ipynb(405KB)
--------8.2-deep-dream.ipynb(196KB)
--------3.5-classifying-movie-reviews.ipynb(68KB)
--------6.1-using-word-embeddings.ipynb(92KB)
--------6.2-understanding-recurrent-neural-networks.ipynb(83KB)
--------6.4-sequence-processing-with-convnets.ipynb(92KB)
--------8.1-text-generation-with-lstm.ipynb(157KB)
--------6.3-advanced-usage-of-recurrent-neural-networks.ipynb(199KB)
--------8.5-introduction-to-gans.ipynb(144KB)
--------4.4-overfitting-and-underfitting.ipynb(104KB)
--------6.1-one-hot-encoding-of-words-or-characters.ipynb(9KB)
--------5.3-using-a-pretrained-convnet.ipynb(228KB)
--------8.4-generating-images-with-vaes.ipynb(277KB)
--------5.4-visualizing-what-convnets-learn.ipynb(6.68MB)
--------3.7-predicting-house-prices.ipynb(69KB)
--------3.6-classifying-newswires.ipynb(62KB)
--------5.1-introduction-to-convnets.ipynb(11KB)
--------2.1-a-first-look-at-a-neural-network.ipynb(14KB)
----LICENSE(1KB)
----chapter04_getting-started-with-neural-networks.ipynb(29KB)
----chapter09_part03_interpreting-what-convnets-learn.ipynb(19KB)
----chapter11_part03_transformer.ipynb(12KB)
----chapter11_part01_introduction.ipynb(18KB)
----chapter13_best-practices-for-the-real-world.ipynb(10KB)
----chapter12_part02_deep-dream.ipynb(7KB)
----chapter12_part01_text-generation.ipynb(14KB)
----chapter12_part03_neural-style-transfer.ipynb(10KB)
----README.md(5KB)
----chapter10_dl-for-timeseries.ipynb(21KB)
----chapter03_introduction-to-keras-and-tf.ipynb(20KB)
----chapter05_fundamentals-of-ml.ipynb(18KB)
----chapter09_part02_modern-convnet-architecture-patterns.ipynb(6KB)