11.9 Train vs Validation vs Test Set | Parameters vs Hyperparameters in ML

This video explains the train, validation, and test sets along with the difference between model parameters and hyperparameters. Learn how to properly split data and evaluate machine learning models for better performance.

Topics Covered:
1. Introduction to Machine Learning
2. Model Parameters vs Hyperparameters
3. Train, Validation & Test Sets – Concepts
4. Use-cases of Data Splitting
5. Why Do We Need a Test Set?
6. Train, Validation & Test Split Using Python
7. Best Practices for Data Splitting
Helpful For:
1. Cracking AI / ML / Data Science interview rounds at top tech companies
2. Building a deeper understanding of core AI, ML concepts
3. Preparing for GATE (DA / CS / Other streams) and other related competitive exams
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Tags:
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Видео 11.9 Train vs Validation vs Test Set | Parameters vs Hyperparameters in ML канала Decode AiML