This new workshop will give you an overview of how to deal with regression problems.
Regression can be used when the target (the variable that will be predicted) is numerical.
There are different regression algorithms that can be used to predict numerical data and you will be able to compare the results of three of them during the Lab.
To perform this Lab, we will use a set of car import data to predict the price of a car. This data set contains 205 records, from which you will define your Data Sets (Training, Testing …).
You will learn the steps to explore and prepare the data, create a model and use Watson Machine Learning Client to save and deploy the model in the IBM Cloud.
This Lab uses Python 3.7 as well as Scikit-learn. Three regression algorithms will be implemented :
* Linear regression
* “Support Vector Regression”
* Decision tree
This workshop will be led by Georges-Henri Moll, IBM Digital Developer Advocate – Data Scientist – Master Inventor (https://www.linkedin.com/in/georgeshenrimoll/?originalSubdomain=fr).