Machine Learning using Python Training

Module 1 - Machine Learning vs Statistical Modeling & Supervised vs Unsupervised Learning

• Machine Learning Languages, Types, and Examples 

• Machine Learning vs Statistical Modelling

• Supervised vs Unsupervised Learning 

• Supervised Learning Classification 

• Unsupervised Learning 

Module 2 - Supervised Learning I

• K-Nearest Neighbors 

• Decision Trees 

• Random Forests

• Reliability of Random Forests 

• Advantages & Disadvantages of Decision Trees  

 Module 3 - Supervised Learning II

• Regression Algorithms 

• Model Evaluation 

• Model Evaluation: Overfitting & Underfitting

• Understanding Different Evaluation Models 

 Module 4 - Unsupervised Learning

• 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 

Module 5 - Dimensionality Reduction & Collaborative Filtering

• Dimensionality Reduction: Feature Extraction & Selection 

• Collaborative Filtering & Its Challenges