Data Science & Machine Learning - 1 Installation Process

Hi friends,

Welcome to another post under Data Science & Machine Learning. In the previous post, we discussed an overview of what all things we are going to learn through the series of posts under Data Science & Machine Learning. In this post, we’ll go through the installation process of Python and Jupyter Notebook.

We’ll use the latest Python 3 version provided by the Anaconda distribution. Anaconda is the leading open data science platform powered by Python. The open source version of Anaconda is a high performance distribution of Python and R and includes over 100 of the most popular Python, R and Scala packages for data science.

For doing the programming in Python, we’ll be using the Jupyter Notebook. You are however allowed to use any of your favorite python editors such as PyCharm or any other text editor. The Jupyter Notebook is an open-source web application that allows you to create documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more.

Installation Process

Now, we head over to the installation process of the Jupyter Notebook. The installation process of Jupyter through Anaconda distribution includes installation of both latest Python 3 version and Jupyter Notebook. The installation can be done through the following link.

You need to follow the process under the heading 'Installing Jupyter using Anaconda and conda'. 

After you are done installing, you can see if everything went right by opening command prompt in Windows and typing jupyter notebook in the command prompt. It will open a browser tab appearing like one below:

It might take a little time to open the browser tab so have a bit of patience. In the next post, we will review some basic concepts in Python that are later required for Data Science & Machine Learning.