{"id":19694142,"url":"https://github.com/innofang/tensorflow2-from-zero","last_synced_at":"2026-06-16T07:31:54.253Z","repository":{"id":129983689,"uuid":"286366239","full_name":"InnoFang/tensorflow2-from-zero","owner":"InnoFang","description":"Learn TensorFlow 2.0","archived":false,"fork":false,"pushed_at":"2021-01-30T13:34:29.000Z","size":33859,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-27T12:39:00.496Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# tensorflow2-from-zero\n\nTensorFlow 2.0 学习笔记\n\n\u003e 温馨提示：如果 clone 速度过慢，可以使用以下命令\n\u003e \n\u003e `git clone --depth 1 https://github.com.cnpmjs.org/InnoFang/tensorflow2-from-zero.git`\n\n + 01. 数据类型、张量、函数 -\u003e [Overview.ipynb](01.%20Overview.ipynb)\n + 02. 用神经网络训练鸢尾花数据集 -\u003e [Iris Classification.ipynb](02.%20Iris%20Classification.ipynb)\n + 03. 激活函数 -\u003e [Activator.ipynb](03.%20Activator.ipynb)\n + 04. 损失函数 -\u003e [Loss Function.ipynb](04.%20Loss%20Function.ipynb)\n + 05. 正则化 -\u003e [Regularizer.ipynb](05.%20Regularizer.ipynb)\n + 06. 优化器 -\u003e [Optimizer.ipynb](06.%20Optimizer.ipynb)\n + 07. 使用 tf.keras “六步法”搭建神经网络 -\u003e [Keras Basic.ipynb](07.%20Keras%20Basic.ipynb)\n + 08. 使用 tf.keras 来训练 MNIST 数据集 -\u003e [MNIST.ipynb](08.%20MNIST.ipynb)\n + 09. 对“六步法”搭建神经网络进行扩展 -\u003e [Keras Advanced.ipynb](09.%20Keras%20Advanced.ipynb)\n + 10. 对卷积神经网络进行介绍 -\u003e [CNN.ipynb](10.%20CNN.ipynb)\n + 11. 用 CNN 训练 Fashion MNIST 数据集 -\u003e [CIFAR-10.ipynb](11.%20Fashion%20MNIST.ipynb)\n + 12. 使用 LeNet 训练 Fashion MNIST 数据集 -\u003e [LeNet.ipynb](12.%20LeNet.ipynb)\n + 13. 使用 AlexNet 训练 Fashion MNIST 数据集 -\u003e [AlexNet.ipynb](13.%20AlexNet.ipynb)\n + 14. 使用 VGGNet 训练 Fashion MNIST 数据集 -\u003e [VGGNet.ipynb](14.%20VGGNet.ipynb)\n + 15. 使用 InceptionNet 训练 Fashion MNIST 数据集 -\u003e [InceptionNet.ipynb](15.%20InceptionNet.ipynb)\n + 16. 使用 ResNet 训练 Fashion MNIST 数据集 -\u003e [ResNet.ipynb](16.%20ResNet.ipynb)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finnofang%2Ftensorflow2-from-zero","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Finnofang%2Ftensorflow2-from-zero","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finnofang%2Ftensorflow2-from-zero/lists"}