Introduction and Regression      

• Introduction
• Anaconda
• Regression
  • Scikit-Learn
  • Correlation Analysis and Feature Selection
  • Linear Regression with Scikit-Learn
  • Robust Regression
  • Evaluate Regression Model Performance
  • Multiple Regression
  • Polynomial Regression
  • Dealing with Non-linear Relationships
  • Data Pre-processing

Classification and Clustering      

• Classification
  • Introduction to Classification
  • Understanding MNIST
  • Stochastic Gradient Descent (SGD)
  • Confusion Matrix
  • Precision
  • Recall
  • F1 Score
  • Precision Recall Trade-off
• Clustering

Support Vector Machine and Tree          

• Support Vector Machine
  • Support Vector Machine (SVM) Concepts
  • Linear SVM Classification
  • Support Vector Regression
  • Polynomial Kernel
• Tree
  • Introduction to Decision Tree
  • Training and Visualizing a Decision Tree
  • Visualizing Boundary
  • Tree Regression, Regularization and Over Fitting
  • End to End Modelling

Ensemble Machine Learning      

• Ensemble Machine Learning
  • Ensemble Learning Methods Introduction
  • Bagging
  • AdaBoost
  • Gradient Boosting Machine
  • XGBoost
  • Random Forests and Extra-Trees