About this course
In this highly competitive global environment, any professional and progressive organization that aims to grow significantly cannot depend solely on qualitative methods of prediction. Instead, robust quantitative methods that model large amounts of data can be used for more accurate prediction. Predictive Modeling encompasses a variety of techniques that can be used by organizations to predict continuous (for example, sales or demand data) as well as categorical (is someone a buyer or non-buyer?) dependent variables based on a host of input variables (independent variables).
Predictive Modeling and Analytics
- Overview of Predictive Modelling
- Understanding Regression
- Regression using R
- Logistic Regression
- Logistic Regression using R
- Introduction to Linear Discriminant Analysis (LDA)
- LDA in R
- Frequency Based Algorithm
- Frequency Based Algorithms in R
- Model Comparison
- Cross Validation
- Cross Validation in R
Predict future election outcomes
The dataset used in this project is Historical election data.The objective of the project is to predict the results of a forthcoming election in India using machine learning algorithms on historical election data.
Get Predictive Modeling and Analytics course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.