One of the most popular environment managers for Python users is Anaconda. With Anaconda, it's straightforward to set up, switch, and delete environments. Therefore, one can easily run Python 2 and Python 3 on the same machine and switch between different installed versions of installed libraries if needed. In this book, we purely focus on Python 3 and every recipe can be run within one environment: environment-python-deep-learning-cookbook.
Installing Anaconda and libraries
How to do it...
- You can directly download the installation file for Anaconda on your machine as follows (adjust your Anaconda file accordingly):
curl -O https://repo.continuum.io/archive/Anaconda3-4.3.1-Linux-x86_64.sh
- Next, run the bash script (if necessary, adjust the filename accordingly):
bash Anaconda3-4.3.1-Linux-x86_64.sh
Follow all prompts and choose 'yes' when you're asked to to add the PATH to the .bashrc file (the default is 'no').
- Afterwards, reload the file:
source ~/.bashrc
- Now, let's set up an Anaconda environment. Let's start with copying the files from the GitHub repository and opening the directory:
git clone https://github.com/indradenbakker/Python-Deep-Learning-Cookbook-Kit.git
cd Python-Deep-Learning-Cookbook-Kit
- Create the environment with the following command:
conda env create -f environment-deep-learning-cookbook.yml
- This creates an environment named environment-deep-learning-cookbook and installs all libraries and dependencies included in the .yml file. All libraries used in this book are included, for example, NumPy, OpenCV, Jupyter, and scikit-learn.
- Activate the environment:
source activate environment-deep-learning-cookbook
- You're now ready to run Python. Follow the next recipe to install Jupyter and the deep learning frameworks used in this book.
