L - 2.7 : Feature Scaling & Feature Selection in Machine Learning | Forward & Backward Selection

Описание: In this video, we explain Feature Scaling and Feature Selection in Machine Learning in a simple and intuitive manner with practical understanding.

You will clearly understand why feature selection is important, how it improves model accuracy, reduces overfitting, and makes models more interpretable.

🔍 Topics covered in this video:
✔ What are features in Machine Learning?
✔ Why do we need feature scaling?
✔ What is feature selection and why is it important?
✔ Best Subset Selection method
✔ Forward Stepwise Selection
✔ Backward Stepwise Selection
✔ Comparison between Forward & Backward Selection

This video is extremely useful for:
🎯 Machine Learning beginners
🎯 Data Science students
🎯 Engineering & MCA students
🎯 GATE / University exam preparation
🎯 Anyone preparing for ML interviews

📌 The explanation is in Hindi, making it easy for students across India and worldwide to understand complex Machine Learning concepts effortlessly

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Machine Learning | Data Science | Algorithms | Core Computer Science

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