Machine learning vs. Statistical modelling
Supervised vs. Unsupervised Learning
• Machine Learning Languages, Types, and Examples
• Machine Learning vs Statistical Modelling
• Supervised vs Unsupervised Learning
• Supervised Learning Classification
• Unsupervised Learning
Supervised Learning
• Understanding nearest neighbour classification
• The KNN algorithm
• Measuring similarity with distance
• Choosing Appropriate K
• Use Case
Classification Using Naïve Bayes
• Basic Concepts of Bayesian Methods
• Probabilistic Learning
Classification using Decision Trees
• The C5.0 decision tree algorithm
• Understanding Classification Rules
• Separate and Conquer
• Rules from decision trees
• Advantages & Disadvantages of Decision Trees
Understanding Regression
• Simple Linear Regression
• Ordinary least Square estimation
Correlations
Multiple Linear Regression
Support Vector Machines
• Classification with Hyper planes
• Using Kernels for non-linear spaces
Neural Networks
• Black Box Methods
• Training neural networks with back propagation
Unsupervised Learning
Association Rules – Pattern detection
• K-Means Clustering plus Advantages & Disadvantages
• Hierarchical Clustering plus Advantages & Disadvantages
• Measuring the Distances Between Clusters – Single Linkage Clustering
• Measuring the Distances Between Clusters – Algorithms for Hierarchy Clustering
• Density-Based Clustering
Evaluating Model Performance
Improving Model Performance
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