Imbalanced Classification

What you'll be able to do

• 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

1. 01Introduction4 lessons · 16 min

   1. Problem with Imbalanced ClassesPreview4:49
   2. ResourcesPreview1:46
   3. Build and examine baselinePreview8:27
   4. Download Resources1:00
2. 02Sampling Based Approaches12 lessons · 1 h 10 min

   1. Approach 1: Upsampling the minority classPreview7:18
   2. Approach 2: Downsampling the majority class6:15
   3. Approach 3: Cluster Centroids - TheoryPreview11:54
   4. Code Demo3:46
   5. Approach 4: SMOTE Algorithm Theory5:50
   6. Code Demo6:43
   7. Approach 5: ADASYN Algorithm Theory11:50
   8. Code Demo3:07
   9. Approach 6: Near Miss5:35
   10. Approach 7: Tomek Links2:30
   11. Code Demo3:55
   12. Course Review1:00
3. 03Class Sensitive Learning Approaches3 lessons · 19 min

   1. Class Sensitive Learning Theory6:27
   2. Code Demo4:18
   3. Class Weighted XGBoost and Demo8:29
4. 04Advanced Methods7 lessons · 1 h 4 min

   1. One Class Classification Theory4:14
   2. One Class using SVM8:24
   3. Mahalanobis Distance for One Class Classification10:44
   4. Isolation Forest Demo9:56
   5. Data Leakage - A sneaky surprisingly hard to detect example8:13
   6. Edited Nearest Neighbour based example11:44
   7. Probability Threshold Tuning10:55

What you need

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

Who this course is for

• Data Science Aspirants
• Data Science Professionals
• Software/Data engineers interested in quantitative analysis
• Professionals working with large datasets
• Data analysts, economists, researchers

Your instructor

Prabhakaran S

Principal Data Scientist

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

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 and 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 on-the-job experience. Hope you love it!

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