Machine Learning for Engineering & Science Applications | IIT Madras - #81 Gradient Boosting | 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 discusses gradient boosting, a machine learning technique that combines multiple weak learners to create a strong learner. The algorithm iteratively adds new models to the ensemble, with each new model trained to correct the errors made by the previous models. Gradient boosting can be used for both regression and classification problems.
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