How to Handle Imbalanced Data | Machine Learning Interview Questions In Hindi
Автор: AI SayI
Загружено: 2025-09-17
Просмотров: 5
Описание:
Struggling with imbalanced datasets in your machine learning projects? This is a classic interview question and a real-world challenge for AI/ML engineers. In this video, we break down the 6 key strategies you MUST know to handle imbalanced data effectively.
Whether you're preparing for a technical interview or looking to build more robust models, this guide will walk you through the essential techniques from resampling to choosing the right evaluation metrics.
✅ *Techniques Covered in This Video:*
The Problem with Imbalanced Data
Resampling Techniques (Oversampling & Undersampling)
Class Weighting in Your Loss Function
Anomaly Detection Approaches
Using Algorithms Robust to Imbalance
Choosing the Right Evaluation Metrics (F1, AUC, etc.)
Data Curation for Better Representation
Key Takeaways & Summary
💬 *Got questions?* Drop them in the comments below! I do my best to answer every single one.
🔔 *Subscribe for more practical AI/ML interview prep and concepts:*
#MachineLearning #DataScience #AI #InterviewPrep #ImbalancedData
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