MACHINE LEARNING
DOWNLOAD MATERIALS :
PROFESSOR : Haim Schweitzer
TOPICS :
• Decision Trees
• Neural Networks
• Deep Learning
• Evaluation of Learning Algorithms
• Bayesian and Naive Bayesian Learning
• Nearest Neighbors Algorithms
• Linear Discriminants
• Computational Learning Theory
• Adaptive Boosting.
• Support Vector Machines.
• Reinforcement Learning
• Unsupervised learning (clustering)
PROFESSOR : Haim Schweitzer
TOPICS :
• Decision Trees
• Neural Networks
• Deep Learning
• Evaluation of Learning Algorithms
• Bayesian and Naive Bayesian Learning
• Nearest Neighbors Algorithms
• Linear Discriminants
• Computational Learning Theory
• Adaptive Boosting.
• Support Vector Machines.
• Reinforcement Learning
• Unsupervised learning (clustering)