In this video, I clearly explain Encoding in Machine Learning in simple Telugu with practical examples.
Machine Learning models understand only numbers.
So how do we convert categorical data like City, Gender, Education into numbers?
In this video, you will learn:
✅ What is Encoding in ML
✅ Why encoding is required
✅ Label Encoding – when to use & when not to use
✅ One-Hot Encoding – advantages & disadvantages
✅ False ranking problem in Label Encoding
✅ High dimensionality problem in One-Hot Encoding
✅ Practical implementation using Pandas & Sklearn
✅ Interview questions on encoding
This video is perfect for:
• ML beginners
• Data Science students
• AI job aspirants
• Anyone learning Machine Learning in Telugu
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