Wall Street Oasis course: Applied Machine Learning Algorithms - Advanced

Data Cleaning & Exploration :

• Identify and correct errors in categorical variables
• Identify and correct errors in continuous variables
• Eliminate sparce classes
• Visualize distribution with and without outliers
• Remove unwanted observations from a dataset
• Identify and eliminate null values in a dataset
• Visualize distributions by class

Liquidity Regressor :

• Split data into training and testing sets
• Construct model pipelines
• Perform hyperparameter tuning
• Cross-validate alternative models (Lasso, Ridge, ElasticNet, RandomForestRegressor, and GradientBoostingRegressor) to find the top performer

Investor Classifier I :

• Understand the business case that is modeled in 'Investor_Classifier_II'
• Perform more advanced data exploration and visualization
• Engineer features based on conditional relationships between existing features

Investor Classifier II :

• Use stratified random sampling to select proportionate samples from categorical data
• Understand the confusion matrix, its relation to the ROC curve and why it is a better success metric than R-squared for classifier algorithms
• Build and finalize a machine elarning classifier from start to finish