Machine Learning for Engineering & Science Applications | IIT Madras - #71 Why LSTM Works? | 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 unveils the magic behind LSTM (Long Short-Term Memory) networks and their effectiveness in tackling the vanishing gradient problem. We'll provide a simplified explanation of how the LSTM architecture mitigates this issue by creating alternate pathways for gradient flow. Drawing parallels with ResNet, we'll illustrate how skip connections facilitate gradient propagation through deeper layers.
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#LSTM #VanishingGradients #ResNet #SkipConnections
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