Course Content
Identifying Fake News
Initial Model Fit
Now that we have prepared our data, the time has come to train our algorithm. We will start by splitting our data into training and testing sets, then train a Logistic Regression model as a starting point for our analysis.
Task
- Split the data into training and test sets (75% to 25%, respectively).
- Use the appropriate method to train the Logistic Regression model.
- Make predictions using the Logistic Regression model on the test set.
Task
- Split the data into training and test sets (75% to 25%, respectively).
- Use the appropriate method to train the Logistic Regression model.
- Make predictions using the Logistic Regression model on the test set.
Mark tasks as Completed
Switch to desktop for real-world practiceContinue from where you are using one of the options belowEverything was clear?
Now that we have prepared our data, the time has come to train our algorithm. We will start by splitting our data into training and testing sets, then train a Logistic Regression model as a starting point for our analysis.
Task
- Split the data into training and test sets (75% to 25%, respectively).
- Use the appropriate method to train the Logistic Regression model.
- Make predictions using the Logistic Regression model on the test set.
Mark tasks as Completed
Switch to desktop for real-world practiceContinue from where you are using one of the options belowSection 1. Chapter 5
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