SMOTE: Tackling Imbalanced Data in Machine Learning @stratascratch
SMOTE: Tackling Imbalanced Data in Machine Learning  @stratascratch
Uploaded June 2023 | Updated September 2026, 2 days ago
In this video, we delve into the challenges of imbalanced data in machine learning. Discover effective solutions such as the Synthetic Minority Oversampling Technique (SMOTE) and supplying class weight information to the model during training.

Watch the full tutorial:
πŸ“Œ Data Project: Analyzing Review Sentiment for Accurate Ratings [Part 1]: youtu.be/Qh9ajFNeIEc

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About The Platform:

StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+shorts+s2+p1) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.

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Contact:

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SMOTE: Tackling Imbalanced Data in Machine Learning

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