Azure Machine Learning Online Training

Syllabus of Azure Machine Online Learning Course

• 1. What You Will Learn in This Section
• 2. The course slides as well as Data Files for all sections
• 3. Important Message About Udemy Reviews
• 4. Why Machine Learning is the Future?
• 5. What is Machine Learning?
• 6. Understanding various aspects of data - Type, Variables, Category
• 7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range
• 8. Types of Machine Learning Models - Classification, Regression, Clustering etc
• 9. Basics of Machine Learning

• 1. What You Will Learn in This Section?
• 2. What is Azure ML and high level architecture.
• 3. Creating a Free Azure ML Account
• 4. Azure ML Studio Overview and walk-through
• 5. Azure ML Experiment Workflow
• 6. Azure ML Cheat Sheet for Model Selection
• 7. Getting Started with AzureML

• 1. Data Input-Output - Upload Data
• 2. Data Input-Output - Convert and Unpack
• 3. Data Input-Output - Import Data Data Transform - Add Rows/Columns, Remove Duplicates, Select Columns
• 4. Apply SQL Transformation, Clean Missing Data, Edit Metadata
• 5. Sample and Split Data - Partition or Sample, Train and Test Data
• 6. Update to Lecture Sequence.
• 7. Data Processing

• 1. Logistic Regression - What is Logistic Regression?
• 2. Logistic Regression - Build Two-Class Loan Approval Prediction Model
• 3. Logistic Regression - Understand Parameters and Their Impact
• 4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score
• 5. Logistic Regression - Model Selection and Impact Analysis
• 6. Logistic Regression - Build Multi-Class Wine Quality Prediction Model
• 7. Decision Tree - What is Decision Tree?
• 8. Decision Tree - Ensemble Learning - Bagging and Boosting
• 9. Decision Tree - Parameters - Two Class Boosted Decision Tree
• 10. Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction
• 11. Decision Forest - Parameters Explained
• 12. Two Class Decision Forest - Adult Census Income Prediction
• 13. Decision Tree - Multi Class Decision Forest IRIS Data
• 14. SVM - What is Support Vector Machine?
• 15. SVM - Adult Census Income Prediction
• 16. Classification Quiz

• 1. Tune Hyperparameter for Best Parameter Selection
• 2. Hyperparameter Tuning

• 1. Azure ML Webservice - Prepare the experiment for webservice
• 2. Deploy Machine Learning Model As a Web Service
• 3. Use the Web Service - Example of Excel
• 4. AzureML Web Service

• 1. What is Linear Regression?
• 2. Regression Analysis - Common Metrics
• 3. Linear Regression model using OLS
• 4. Linear Regression - R Squared
• 5. Gradient Descent
• 6. Linear Regression: Online Gradient Descent
• 7. Experiment Online Gradient
• 8. Decision Tree - What is Regression Tree?
• 9. Decision Tree - What is Boosted Decision Tree Regression?
• 10. Decision Tree - Experiment Boosted Decision Tree
• 11. Regression Analysis

• 1. What is Cluster Analysis?
• 2. Cluster Analysis Experiment 1
• 3. Cluster Analysis Experiment 2 - Score and Evaluate
• 4. Clustering or Cluster Analysis

• 1. Section Introduction
• 2. How to Summarize Data?
• 3. Summarize Data - Experiment
• 4. Outliers Treatment - Clip Values
• 5. Outliers Treatment - Clip Values
• 6. Clean Missing Data with MICE
• 7. Clean Missing Data with MICE
• 8. SMOTE - Create New Synthetic Observations
• 9. Data Normalization - Scale and Reduce
• 10. Data Normalization
• 11. PCA - What is PCA and Curse of Dimensionality?
• 12. Principal Component Analysis
• 13. Join Data - Join Multiple Datasets based on common keys
• 14. Join Data - Experiment

• 1. Feature Selection - Section Introduction
• 2. Pearson Correlation Coefficient
• 3. Chi Square Test of Independence
• 4. Kendall Correlation Coefficient
• 5. Spearman's Rank Correlation
• 6. Comparison Experiment for Correlation Coefficients
• 7. Filter Based Selection - AzureML Experiment
• 8. Fisher Based LDA - Intuition
• 9. Fisher Based LDA - Experiment