Machine Learning Fundamentals: Bias and Variance | Overfitting and Underfitting Explained | NerdML
This video will help you to understand What is Bias & how does it work? What is variance & how to mathematically calculate variance on data-points? What is Overfitting & Underfitting? How to avoid Overfitting & Underfitting by trading-off bias-variance.
Bias and Variance are two fundamental concepts for Machine Learning, and their intuition is just a little different from what you might have learned in your statistics class. Here I go through two examples that make these concepts super easy to understand.
Below topics are explained in this video:
1. What is Bias & how does it work? ( 00:23 )
2. What is variance & how to mathematically calculate variance on data-points? ( 02:17 )
3. What is Overfitting & Underfitting? ( 04:55 )
4. How to avoid Overfitting & Underfitting by trading-off bias-variance? (10:58)
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Prerequisites
Basic understanding of Linear Algebra, Probability, Calculus, Matrix & Python programming including pandas, numpy, scikit learn & some visualisation tools.
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Creator : Rahul Saini
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