Python
The structure is clear, simple and easy to learn, with a rich ecosystem of standard libraries and third-party libraries, which is very suitable as a programming language for machine learning algorithms .
However, because Python is a general-purpose interpreted language, the efficiency of implementing complex algorithms will be greatly limited. Therefore, in actual machine learning and deep learning projects, more efficient implementation methods need to be used. Tensor Flow is an efficient artificial intelligence development framework launched by Google . Until the release of TensorFlow 2.0, its ease of use has been greatly improved.
ANACONDA development environment
Install TensorFlow from the command line
Step 1: Create an independent environment and activate
conda create --name tensorflow2.0 python==3.7
activate tensorflow2.0
Step 2: Install related software packages
pip install numpy matplotlib Pillow scikit-learn pandas -i https://pypi.tuna.tsinghua.edu.cn/simple
Step 3: Install TensorFlow2.0
pip install tensorflow==2.0.0-beta -i https://pypi.tuna.tsinghua.edu.cn/simple
Step 4: Test TensorFlow2.0
Enter python in the command line to open the python interactive mode
Input code: import tensorflow
If there are no errors, the installation is successful