Machine Learning (AL405)-CSE (IV) | RGPV

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• Syllabus

• Syllabus - Machine Learning (AL405)

• Introduction to machine learning

• Introduction and Scope of Machine Learning
• Machine Learning Models
• Hypothesis Space and Inductive Bias
• Evaluation and Cross-Validation
• Dimensionality Reduction

• Neural Networks

• Introduction to Neural Networks
• Perceptron Learning
• Multilayer Perceptron and Back Propagation
• Activation Functions and Gradients

• Supervised Learning Techniques

• Decision Trees and Naive Bayes
• Classification Techniques
• Regression Techniques

• Unsupervised Learning and Clustering

• Introduction to Unsupervised Learning
• Clustering Techniques
• Optimization and Advanced Clustering

• Design and Analysis of Machine Learning Experiments

• Experiment Design in Machine Learning
• Cross-Validation and Resampling
• Performance Measurement and Hypothesis Testing