Machine Learning for Engineering & Science Applications | IIT Madras - #47 Introduction to Back Prop | 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 introduces the concept of backpropagation, which is an algorithm for training neural networks. Backpropagation uses the chain rule from calculus to calculate the gradients of the network's weights. This is used to update the weights to minimize the loss function.
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#Backpropagation #ChainRule #AutomaticDifferentiation #NeuralNetwork #ForwardPass
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