laptop with gpu for deep learning

path=/usr/local/cuda-8.0/bin/: $PATHExport ld_library_path= "/usr/local/cuda-8.0/lib64:/usr/local/cuda-8.0/extras/cupti/lib64"Installation CUDNN is relatively simple, after extracting the corresponding files copied to the corresponding Cuda directory can besudo cp cudnn.h/usr/local/cuda/include/#复制头文件sudo cp lib*/usr/local/cuda/lib64/#复制动态链接库sudo rm-rf libcudnn.so libcudnn.so.6 #删除原有动态文件sudo ln-s libcudnn.so.6.0.21 libcudnn.so.6 #生成软链接sudo ln-s libcudnn.so.6 libcudnn.so #生成软链接Installing Minicon

installation was successful, import the NumPy with Python, as follows to complete the installation4. Installing TensorFlow1.> download the corresponding version of the TensorFlow, must be corresponding to the Python version, the latest is the support python3.6 version, for: https://pypi.org/project/tensorflow-gpu/#files, Because my Python version is 3.6, so download TENSORFLOW_GPU-1.8.0-CP36-CP36M-WIN_AMD64.WHL2.> Installation: command: Pip install T