11. How to Handle Imbalanced Data in Machine Learning (Dataset Given) | Oversampling & Undersampling

📂 Dataset used in this video: Check Pinned comment. In this video, we learn how to handle Imbalanced Datasets in Machine Learning using Oversampling and Undersampling techniques. This tutorial includes: • What is an imbalanced dataset • Why imbalanced data is a problem • Oversampling explained • Undersampling explained • Practical implementation using Python • Real dataset demonstration This video is part of the Supervised Learning playlist in our AIML Course by NexTechX, where complex concepts are explained in a simple and practical way. 💻 Tools used: • Python • Pandas • Scikit-learn • imbalanced-learn (imblearn) 🚀 Related videos: • Confusion Matrix • Logistic Regression • Classification Basics 🔔 Subscribe for more AI/ML tutorials: www.youtube.com/@UCwyO9DDxS11azcManaNp3Rw #MachineLearning #Python #DataScience #ImbalancedDataset #Oversampling #Undersampling #AIML