Installation Documentation for Python

You will need various Python packages (or synonymously, libraries) for specific purposes. 

Anaconda is an open-source distribution that simplifies package management and deployment. The package management system 'Conda' manages package versions.

We strongly recommend using Anaconda to install Python as well as the packages, since it comes preloaded with most of the packages you will need.

Advantages of using Anaconda

1. It is easy to manage and supports most of the libraries required for Machine learning/Artificial Intelligence problems. 

2. Anaconda comes with many libraries such as NumPy, OpenCV, SciPy, PyQt, the Spyder IDE, etc.

Anaconda can be downloaded from anaconda.org and can be installed like any other normal software. There is no need to download Python separately; the Anaconda installer will do this for you. Make sure you select Python 3.x while downloading Anaconda.

Note for experienced Python programmers: In case you're already using Python along with an existing package manager such as pip or easy_install, you can continue to do so. However, make sure you're using Python 3.x.

Jupyter Notebook

You’ll use the Jupyter IPython Notebook as the main environment for writing Python code throughout this program. The key advantage of using Jupyter Notebook is that you can write both code and normal text (using the Markdown format in Jupyter) in the notebooks. These notebooks are easy to read and share, and can even be used to present your work to others. Here’s a brief overview of Jupyter Notebook.

The document given below provides instructions for installing Python and the Jupyter Notebook using Anaconda.

Also, refer to the document for help with installing Anaconda successfully. It is important to note that you need to install Python 3.x (the latest 3.x version available), not 2.x.

Please proceed to the next segment only after installing Anaconda and the Jupyter notebook.

Additional Reading

If you want to know about Jupyter notebook in brief check out this link:

Jupyter Notebook quick starter guide