Скачать или смотреть Cross Validation in Machine Learning | Theory Explained | Module 3 Part 5 (KTU AMT305)

📌 Welcome to Module 3 Part 5 of the Machine Learning series (KTU AMT305 – 2019 Scheme)!
In this video, we explain the concept of Cross Validation — a key model evaluation technique used to test the performance and generalization ability of Machine Learning models.

This session includes clear theoretical explanations with K-Fold Cross Validation and Leave-One-Out Cross Validation (LOOCV), helping you easily understand how these methods work step by step.



🎯 Topics Covered:

✔️ What is Cross Validation in Machine Learning?
✔️ Why Cross Validation is Important
✔️ K-Fold Cross Validation – Step-by-Step Explanation
✔️ Leave-One-Out Cross Validation (LOOCV)
✔️ Comparison Between Bootstrapping and Cross Validation
✔️ Advantages and Limitations of Cross Validation
✔️ Example for Better Understanding



👨‍🎓 Who is this for?

KTU AI & DS 5th Semester Students (2019 Scheme)
Beginners learning ML model evaluation techniques
Students preparing for **AMT305 theory exams



📘 Subject: Introduction to Machine Learning
📚 Course Code: AMT305
🎓 University: APJ Abdul Kalam Technological University (KTU – 2019 Scheme)



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