Welcome to Predictive Modeling, Model Fitting, and Regression Analysis. In this course, we will explore different approaches in predictive modeling, and discuss how a model can be either supervised or unsupervised. We will review how a model can be fitted, trained and scored to apply to both historical and future data in an effort to address business objectives. Finally, this course includes a hands-on activity to develop a linear regression model.
This course is part of the Data Science Fundamentals Specialization
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About this Course
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Try Coursera for BusinessWhat you will learn
The application of predictive modeling to professional and academic work
Applications of classification analysis: decision trees
Applications of regression analysis (linear and logistic)
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Predictive Modeling
Data Dimensionality and Classification Analysis
Model Fitting
Regression Analysis
Reviews
- 5 stars67.34%
- 4 stars16.32%
- 3 stars8.16%
- 2 stars4.08%
- 1 star4.08%
TOP REVIEWS FROM PREDICTIVE MODELING, MODEL FITTING, AND REGRESSION ANALYSIS
course content is very concise and easy to understand
Thank you Very Much I learn a lot of Thing with all kinds of Predative Modeling that I can use.
good course to understand the fundamentals of predictive analysis
About the Data Science Fundamentals Specialization

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