How to build machine learning models for imbalanced datasets

In this video, we will explore the important topic of how we can build machine learning models for imbalanced datasets. Particularly, for classification problem where the classes are imbalanced we can perform class balancing (either via undersampling or oversampling). This video benchmarks or compares various class balancing approaches along with the imbalanced dataset as a control for model building. Code https://github.com/dataprofessor/machine-learning-for-imbalanced-data 🌟 Join as a Channel Member to support us: https://www.youtube.com/channel/UCV8e2g4IWQqK71bbzGDEI4Q/join 🌟 Download Kite for FREE https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=dataprofessor&utm_content=description-only ⭕ Watch this video next: - How to Master Python for Data Science https://youtu.be/AeUnO1oNv08 ⭕ Support my work: 🌟 Subscribe to the Coding Professor channel https://www.youtube.com/channel/UCJzlfIoF8nmWqJIv_iWQVRw?sub_confirmation=1 🌟 Subscribe to the Data Professor channel https://www.youtube.com/dataprofessor?sub_confirmation=1 🌟 Join the Newsletter of Data Professor http://newsletter.dataprofessor.org 🌟 Buy me a coffee https://www.buymeacoffee.com/dataprofessor ⭕ Recommended Books: 🌟https://kit.co/dataprofessor ✅ Python Basics: A Practical Introduction to Python 3 https://amzn.to/3awdWgm ✅ Learn Python Programming (The no-nonsense, beginner's guide) https://amzn.to/2RFpSpn ✅ Learn to Program with Minecraft https://amzn.to/3x2MujZ ✅ Automate the Boring Stuff with Python, 2nd Edition: Practical Programming for Total Beginners https://amzn.to/2QzkyDs ⭕ Disclaimer: Recommended books and tools are affiliate links that gives me a portion of sales at no cost to you, which will contribute to the improvement of this channel's contents. Balance icon from Flaticon https://www.flaticon.com/free-icon/comparison_923051?related_id=923051 ⭕ Stock photos, graphics and videos used on this channel: ✅ https://1.envato.market/c/2346717/628379/4662 #datascience #machinelearning #dataprofessor