Imbalanced Classification

  • Have you come across the problem of class imbalance while working on classification problems?
    Learn how to solve this problem and make classification engines to classify the target variable
    even on the imbalanced data.

Created by Selva Prabhakaran

  • 30 Video Lessons

  • English

  • English captions

What you will learn

01

What is class imbalance and why is it a problem?

02

Perform upsampling and downsampling from scratch

03

What is hybrid sampling and How is it different?

04

One class classification approaches for imbalanced classification

05

Learn advanced sampling
techniques like SMOTE, ADASYN, TOMEK LINKS..

06

Know the parameters of algorithms to handle imbalance data

07

Learn advanced classification algorithms for imbalanced data

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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