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43 lines
1.5 KiB
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43 lines
1.5 KiB
Markdown
# Tensorflow学习
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## 安装GPU版Tensorflow方法
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1. 安装Python：python-3.7.4-amd64.exe。
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下载地址：https://www.python.org/downloads/release/python-374/
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2. 安装CUDA 10.0。
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下载地址：https://developer.nvidia.com/cuda-10.0-download-archive
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注意：要安装GPU驱动、CUDA工具包、CUDA附带的CUPTI。
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3. 安装CUDNN 7.6.2。
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下载地址：https://developer.nvidia.com/rdp/cudnn-archive
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4. 安装GPU版Tensorflow。
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```
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pip install tensorflow-gpu==2.0.0-rc0
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```
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## 测试项目
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1. tensorflow/basic/hello_world.py：Hello World示例
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2. tensorflow/basic/calculate.py: 加减乘除运算
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3. tensorflow/basic/calculate_matrix.py: 矩阵运算
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3. tensorflow/basic/mnist_beginer.py: 初学者手写数字识别，准确度:96.3%
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4. tensorflow/basic/mnist_expert.py: 专家级手写数字识别，准确度：98.112%
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5. tensorflow/basic/image_classification.py: 服装图片分类，准确度：87.81%
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6. tensorflow/basic/basic_text_classification.py: 评论文本分类，准确度：86.2%
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7. tensorflow/basic/feature_columns.py: 对结构化数据进行分类，准确度：72.54%
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8. tensorflow/basic/basic_regression.py: 线性回归
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9. tensorflow/basic/overfit_and_underfit.py: 过拟合和欠拟合，准确度：99.99%
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10. tensorflow/basic/save_and_restore_models.py: 保存和恢复模型
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11. tensorflow/basic/intro_to_cnns.py: 卷积神经网络
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## 相关地址
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* 官网: https://pypi.org/project/tensorflow/#history
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* 最新版本: https://pypi.org/project/tensorflow-gpu/#history |