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安装 miniconda
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Conda 环境
- 最简单的
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ conda config --set show_channel_urls yes conda env create --file ./aiclub_mac.yaml source activate aiclub- 或者
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ conda config --set show_channel_urls yes conda create -n aiclub python=3.6 source activate aiclub conda install pandas scikit-learn scikit-image scipy matplotlib sympy jupyter nb_conda -y pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0-py3-none-any.whl pip install tflearn
jupyter notebook --ip='*' --NotebookApp.token= --port=8888- OK
-
安装 miniconda
-
Conda 环境
- 直接导入GPU版本
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ conda config --set show_channel_urls yes conda env create --file ./aiclub_win_gpu.yaml source activate aiclub- 或者直接导入CPU版本
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ conda config --set show_channel_urls yes conda env create --file ./aiclub_win_cpu.yaml source activate aiclub- 当然从头自己装也行
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ conda config --set show_channel_urls yes conda create -n aiclub python=3.6 activate aiclub conda install pandas scikit-learn scikit-image scipy matplotlib sympy jupyter nb_conda -y
下边CPU版本或是GPU版本只需要安装一个，GPU需要Windows安装好CUDA Toolkits并且安装好CUDNN
- GPU版本
pip install --ignore-installed --upgrade tensorflow-gpu pip install tflearn
- CPU版本
pip install --ignore-installed --upgrade tensorflow pip install tflearn
jupyter notebook --ip='*' --NotebookApp.token= --port=8888- OK
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