geektutu / Tensorflow Tutorial Samples
TensorFlow2教程 TensorFlow 2.0 Tutorial 入门教程实战案例
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TensorFlow 2.0 Tutorial 入门教程实战案例
用最白话的语言,讲解机器学习、神经网络与深度学习 示例基于 TensorFlow 1.4 和 TensorFlow 2.0 实现
相关链接
OpenAI gym
-
TensorFlow 2.0 (九) - 强化学习70行代码实战 Policy Gradient
- Github - gym/CartPole-v0-policy-gradient
- 介绍了策略梯度算法(Policy Gradient)来玩 CartPole-v0
-
TensorFlow 2.0 (八) - 强化学习 DQN 玩转 gym Mountain Car
- Github - gym/MountainCar-v0-dqn
- 介绍了DQN(Deep Q-Learning)来玩MountainCar-v0游戏
- Q-Table用神经网络来代替。
-
TensorFlow 2.0 (七) - 强化学习 Q-Learning 玩转 OpenAI gym
- Github - gym/MountainCar-v0-q-learning
- 介绍了使用Q-Learning(创建Q-Table)来玩MountainCar-v0游戏
- 将连续的状态离散化。
-
TensorFlow 2.0 (六) - 监督学习玩转 OpenAI gym game
- Github - gym/CartPole-v0-nn
- 介绍了使用纯监督学习(神经网络)来玩CartPole-v0游戏
- 使用TensorFlow 2.0
mnist
-
TensorFlow 2.0 (五) - mnist手写数字识别(CNN卷积神经网络)
- Github - v4_cnn
- 介绍了如何搭建CNN网络,准确率达到0.99
- 使用TensorFlow 2.0
-
TensorFlow入门(四) - mnist手写数字识别(制作h5py训练集)
- Github - make_data_set
- 介绍了如何使用 numpy 制作 npy 格式的数据集
- 介绍了如何使用 h5py 制作 HDF5 格式的数据集
-
TensorFlow入门(三) - mnist手写数字识别(可视化训练)
- Github - mnist/v3
- 介绍了tensorboard的简单用法,包括标量图、直方图以及网络结构图
-
TensorFlow入门(二) - mnist手写数字识别(模型保存加载)
- Github - mnist/v2
- 介绍了 TensorFlow 中如何保存训练好的模型
- 介绍了如何从某一个模型为起点继续训练
- 介绍了模型如何加载使用,传入真实的图片如何识别
-
TensorFlow入门(一) - mnist手写数字识别(网络搭建)
- Github - mnist/v1
- 这篇博客介绍了使用 TensorFlow 搭建最简单的神经网络。
- 包括输入输出、独热编码与损失函数,以及正确率的验证。
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