Get 80% discount on Machine Learning with Imbalanced Data course from Udemy.
Machine Learning with Imbalanced Data Coupon
Get an exclusive 80% Udemy discount for a limited time
Learn to over-sample and under-sample your data, apply SMOTE, ensemble methods, and cost-sensitive learning.
- Language: English (US)
- Offer: 80% discount
- Total Ratings: 4.8
- Organization: Udemy
- Course Lenght: 11.5 hours on-demand video
What You will learn from this course?
- Apply random under-sampling to remove observations from majority classes
- Perform under-sampling by removing observations that are hard to classify
- Carry out under-sampling by retaining observations at the boundary of class separation
- Apply random over-sampling to augment the minority class
- Create syntethic data to increase the examples of the minority class
- Implement SMOTE and its variants to synthetically generate data
- Use ensemble methods with sampling techniques to improve model performance
- Change the miss-classification cost optimized by the models to accomodate minority classes
- Determine model performance with the most suitable metrics for imbalanced datasets
About Course Instructor
Soledad Galli Soledad Galli is a lead data scientist and founder of Train in Data. She has experience in finance and insurance, received a Data Science Leaders Award in 2018 and was selected “LinkedIn’s voice” in data science and analytics in 2019. Sole is passionate about sharing knowledge and helping others succeed in data science.