Machine Learning for Automobile Applications (EV 504 (a))-Electric Vehicles (V Semester) | RGPV

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• Syllabus

• Syllabus - Machine Learning for Automobile Applications (EV 504 (a))

• Bayesian Decision Theory and Normal Distribution

• Machine Perception
• Classification and Clustering
• Linear and Logistic Regression
• Types of Learning
• Bayesian Decision Theory
• Normal Densities
• Bayesian Belief Networks

• Classification Algorithms

• Perceptron and Backpropagation Neural Network
• Support Vector Machine
• Regression Decision Trees

• Component Analysis and Clustering Algorithms

• Principal Component Analysis
• Linear Discriminant Analysis
• Independent Component Analysis
• K-means Clustering
• Expectation-Maximization Algorithm
• Auto Associative Neural Network

• Supervised and Unsupervised

• Convolution Neural Network (CNN)
• Recurrent Neural Network
• Applications

• Combining Multiple Learners

• Generating Diverse Learners
• Model Combination Schemes