Build a deep learning/machine learning development environment under Linux Ubuntu

First, install the Anaconda

1. Download

For: https://www.anaconda.com/download/#linux

2. Install the anaconda and execute the command:

Bash ~/downloads/anaconda3-5.1.0-linux-x86_64.sh

3. The configuration path is displayed during the installation process

prefix=/home/jsy/anaconda2/

4. After installation, running Python is still the python information of Ubuntu, you need to set the environment variable

5. In the terminal input $sudo gedit/etc/profile, open the profile file

6. Add a line at the end of the file: Export path=/home/jsy/anaconda2/bin: $PATH, where "/home/jsy/anaconda2/bin" is replaced with your actual installation path, save.

7. Restart Linux

8. Open the terminal and enter Python, if the following interface appears, indicating that the setting is successful.

You can also use Conda info to query installation information

Enter Conda list to find out which libraries you have installed now, common Python, NumPy, scipy.

If you still have any packages that are not installed, you can run Conda install (* * * for the package name), and if a package version is not up-to-date, run Conda update * *.

Second, installation Scikit-learn

Execute command:

Conda Install Scikit-learn

Second, installation Kras

Execute command:

Conda Install Keras

The required tensorflow is automatically installation during installation of the Keras process.

At this point, deep learning, machine learning development environment has been installed, you can command

Spyder

Or

Jupyter Notebook

Open your favorite IDE for development, enter the following code, if there is no error, it proves that the environment was installed successfully.

Import Kerasimport Sklearn

　　

Build a deep learning/machine learning development environment under Linux Ubuntu