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Related lectures (7)
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Regression Trees and Ensemble Methods in Machine Learning
Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.
Engineering in the Age of AI: Innovations and Challenges
Examines the transformative impact of AI on engineering disciplines and the associated challenges.
Classification Algorithms: Generative and Discriminative Approaches
Explores generative and discriminative classification algorithms, emphasizing their applications and differences in machine learning tasks.
Decision Trees and Random Forests: Concepts and Applications
Discusses decision trees and random forests, focusing on their structure, optimization, and application in regression and classification tasks.
Machine Learning: Supervised and Unsupervised Learning Techniques
Covers supervised and unsupervised learning techniques in machine learning, highlighting their applications in finance and environmental analysis.
Linear Regression: Foundations and Applications
Introduces linear regression, covering its fundamentals, applications, and evaluation metrics in machine learning.
Generative Models: Advancements in Molecular Design
Explores the use of generative models for discovering novel molecules in molecular design.
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