Introduction
  • What Will You Get From This Course
  • What This Course Is Not
  • What is Machine Learning and Why is it important?
  • Why Rapidminer?
  • What is the difference between Rapidminer Vs Python or R?
Install Rapidminer
  • Installing Rapidminer
Rapidminer Basics
  • Rapidminer Development Environment Introduction
  • Operators, Extensions, Repository, Parameters, Help
  • Let's Build Our First Basic Process - Introduction
  • Let's Build Our First Basic Process - Hands On
  • End of Rapidminer Basics
Predicting House Prices with Regression Algorithm
  • Before We Start
  • Downloading the Data for your First Regression Machine Learning Model
  • What Is This Dataset?
  • Importing Data
  • Partitioning the Data
  • Building Multiple Linear Regression Machine Learning Model
  • Output Results of Multiple Linear Regression Machine Learning Model
  • Validating Performance of Multiple Linear Regression Machine Learning Model
  • Saving your Work
  • Conclusion - First Simple Regression Machine Learning Model
Handling Data Issues for a Regression Model
  • Downloading the Second Dataset With Issues
  • What Is This Dataset?
  • Importing Data and Identifying Issues
  • Eliminating Fields That Are Not Useful
  • Identifying and Removing Outliers
  • Convert Nominal Data Fields to Numerical Data Fields
  • Building Multiple Linear Regression Machine Learning Model on Cleaned Data
Quiz - Linear Regression
  • Let's Test Your Knowledge
Identifying Prospective Customers Using Classification Algorithm
  • Downloading the Data for your First Classification Machine Learning Model
  • What Is This Data?
  • Importing The Data and Identifying The Issues
  • Convert Data From One Type To Another
  • Handling Missing Values In A Field
  • Set Label Role Using Operator
  • Eliminate Fields That Are Not Useful
  • Partition Data and Build Classification Machine Learning Model
  • Output Results of Classification Machine Learning Model
  • Validating Performance of Classification Machine Learning Model
  • Additional Reading
  • Optimizing the Performance of our Classification Machine Learning Model
  • Additional Reading
  • Conclusion - Classification Machine Learning Algorithm
Quiz - Classification
  • Let's Test Your Knowledge
Segmenting Patient Data Using K-Means Clustering
  • What is Clustering and How is it different from Regression or Classification?
  • Download Data for your Clustering Model Example
  • Story behind the data
  • What is K-Means Clustering?
  • Let's Build our Clustering Algorithm to segment patient data
  • Download Data for New Patients
  • Let's Build our Clustering Algorithm to segment patient data - Continued
  • Conclusion
Quiz - Clustering
  • Let's Test Your Knowledge
Predicting Boiler Failures using Anomaly Detection
  • What is an Anomaly?
  • Anomalies are not always bad
  • Download the Data
  • Story behind the Data
  • Exploring our Data
  • Detecting Anomalies Using Statistical Method
  • Detecting Anomalies Using Distance Based Method
  • Detecting Anomalies Using Density Based Method
  • Detecting Anomalies Using Local Outlier Factor Method
  • Conclusion
Quiz - Anomaly Detection
  • Let's Test Your Knowledge
Bonus - Solutions Files
  • Download the Solutions Files
  • How to Use The Solution Files
Section 10 - Thank You
  • Thank You