Imbalanced Classification

Created by Selva Prabhakaran

30 Video Lessons
English
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Validity Period: 365 days

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Self-paced online videos
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Learning duration ~ 2-3 weeks
Complete access for 1 year

What you will learn

What is class imbalance and why is it a problem?

Perform upsampling and downsampling from scratch

What is hybrid sampling and How is it different?

One class classification approaches for imbalanced classification

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

Know the parameters of algorithms to handle imbalance data

Learn advanced classification algorithms for imbalanced data

Course Curriculum

Requirements

Basics of Python
Foundational knowledge of Data Science
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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