First, Make Sure You Follow These Steps, Before Applying Machine Learning Algorithms!

Author(s): Chandra Prakash Bathula

Originally published on Towards AI.

Before applying Machine Learning Algorithms, you should think twice and never forget the data exploration.

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Yes, Exploratory Data Analysis (EDA), is the simple task of analyzing the data using simple data plotting tools based on the concepts of statistics, probability, linear algebra, and other related techniques to understand the data clearly before performing feature engineering and ML modeling.

*** This is one of the extremely important stages that needs to be taken care of for any given case study. The term exploratory suits the operations it performs well.***

Imagine that we are tasked with classifying the flower types and handing over the raw dataset.

How to deal with it? First, we have to explore the data and perform certain operations that reveal insights about the data to understand the following steps to proceed.

We can start basic plotting with a sample dataset to get an intuition.

Why don’t we start with the “Hello World!” of Machine Learning?

Yes, it is about Iris and its classification. Iris can be declared the national flower of the Machine Learning Domain 😂😂😂. Most of the examples you hear about come from the same flower and its types. This dataset is originally from the year 1936.

Even though the flowers look similar, we need to come… Read the full blog for free on Medium.

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Published via Towards AI