Data Pre-processing and EDA

  • Learn how to make the data ready for ML model building and drive actionable business
    insights from the data using extensive EDA

starstarstarstarstar 5.0 (4 ratings)    208 Students

Created by Selva Prabhakaran

  • Last updated 05/2021

  • English

  • English captions

What you will learn

01

What is Data Preprocessing
and Why is it needed?

02

Understand what is EDA
and how to approach

03

Impute missing values
with multiple approaches

04

Understand Outlier
Detection Algorithms

05

Perform statistical
significance tests and interpret

06

Gain knowledge of
Feature encoding and
scaling techniques

07

Create insightful plots
for data analysis

08

End to end EDA for Regression and Classification

Course Curriculum

Requirements

  • Courses Page1 Basics of Python
  • Courses Page1 Foundational knowledge of Data Science
  • Courses Page1 High school maths

Who should attend this course?

  • Data Science Aspirants

  • Data Science Professionals

  • Software/Data engineers interested in quantitative analysis

  • Professionals working with large datasets

  • Data analysts, economists, researchers

Instructor

Selva Prabhakaran Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I’ve put up the series of courses and projects with detailed explanations – just like an on the job experience. Hope you love it!

  • 4.5+Instructor rating

  • 200+ reviews

  • 10K+students

  • 15+ Courses

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