UNIT 1:
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Types of Machine Learning
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Definition of learning systems Goals and applications of machine learning
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Machine Learning Process
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Testing Machine Learning Algorithms
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The Curse of Dimensionality
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Terminology-Weight Space
UNIT 2:
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Regression: Linear Regression,Parametric Models
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Multivariate Regression
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Classification: Bayesian Decision Theory parametric and non-parametric methods
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Multivariate Classification- Logistic Regression
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K-Nearest Neighbor classifier
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Decision Tree based methods for classification & Regression Ensemble methods
UNIT 3:
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Introduction & Clustering
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K-means clustering
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EM algorithm
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Principal Component Analysis
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Hierarchical Clustering
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Probabilistic PCA
