Machine Learning for Engineering & Science Applications | IIT Madras - #29 Bias Variance Trade Off | Machine Learning for Engineering & Science Applications
Unlock the Future: Master AI & Machine Learning with NPTEL-IITM’s Comprehensive Course! Dive into Neural Networks, Deep Learning, Probabilities, and Optimization Techniques tailored for Engineering & Science Applications. Your AI journey starts here!
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What you'll learn
Understand the historical development and foundational concepts of artificial intelligence.
Gain proficiency in applying machine learning techniques to engineering and science problems.
Develop skills in using linear algebra and calculus for machine learning modeling.
Learn to implement and optimize machine learning algorithms using Python packages.
Welcome to 'Machine Learning for Engineering & Science Applications' course !
This lecture explores the crucial concept of the bias-variance trade-off in machine learning. It explains the relationship between model complexity, bias, variance, and generalization error. The lecture uses illustrations to demonstrate how to analyze and manage the bias-variance trade-off, aiming to improve model performance and prevent overfitting or underfitting.
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#BiasVarianceTradeOff #ModelComplexity #Overfitting #Underfitting #GeneralizationError
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