Offered By: IBMSkillsNetwork
Predictive Modeling for Real World Analytics
Predictive modeling allows organizations to make informed decisions and allocate resources effectively by using data to predict future outcomes and trends. In this guided project, you will develop and test multiple prediction models.
Continue readingGuided Project
Data Science
253 Enrolled4.7
At a Glance
Predictive modeling allows organizations to make informed decisions and allocate resources effectively by using data to predict future outcomes and trends. In this guided project, you will develop and test multiple prediction models.
Predictive modeling is a statistical technique that uses data, machine learning algorithms, and modeling techniques. Used by various industries and individuals, predictive modeling is a powerful tool to predict future events.
This guided project comprehensively introduces predictive modeling and its applications in data analysis and decision-making.
You will build and evaluate regression models using the machine learning scikit-learn library and use those models for prediction and decision-making. You will then create exciting visualizations using visualization libraries such as seaborn and matplotlib. Next, you’ll apply built-in methods to model and visualize the data. Then you will create a pipeline to process the data. And you wrap up your guided project by evaluating the effectiveness of your model.Â
A Look at the Project Ahead
After completing this project, you'll be able to:
- Develop prediction models
- Visualize and evaluate created prediction models
What You'll Need
 For this project, you will need:
- Familiarity with fundamentals of data science
- Familiarity with Python fundamentals, Data Structures, and pandas
- A web browserÂ
Your online lab environment has everything you need to get started. Also, note that this platform works best with current versions of modern browsers.