#numpy is a Python library used for working with arrays, created in 2005 by Travis Oliphant. 
#pandas, developed by Wes McKinney in 2008, is an open-source Python library providing high-performance data manipulation and analysis tools using its powerful data structures. 
#matplotlib is one of the most popular Python packages used for data visualization. It is written in Python and makes use of NumPy.

So let’s understand the meme below. Why are these libraries often used in Machine Learning?
A Machine Learning project includes the following tasks:
1. Collecting and Processing Data
2. Exploring the Data to gain insights
3. Modeling the data, Communicating, and Visualizing the results. 

We use NumPy and Pandas for Task1 mainly.
We use Pandas and Matplotlib for Task2 mainly.
And we use Numpy and Matplotlib for Task3 mainly.

Therefore, this is the main reason for them to be constantly used together, the ease with which these libraries can be integrated to perform each task, making it easy for coders to work on any data science project. The other reason is that these libraries are easy to use, as less coding is done and more work is accomplished.

Can you think of any other reasons?? 🤔

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