course content

Course Content

Navigating Data Science Career Paths: A Project for Job Change

1. Data Science Job Change

IntroductionImport DataExploratory Data AnalysisData PreprocessingTrain and Test SplitModel TrainingModel Evaluation

Navigating Data Science Career Paths: A Project for Job Change

Model EvaluationModel Evaluation

Now that we have trained our Logistic Regression algorithm, the next step is to assess the performance. We will compare the true y values with the predicted ones.

The task is completed!

TaskCompleted

  1. Import accuracy_score from sklearn.metrics;
  2. Pass y_test and y_pred to the scoring function.

Congratulations on building your first ML Pipeline. In this project, you have learned how to:

  1. Import your Data;
  2. Visually inspect it;
  3. Preprocess it (clean and impute it);
  4. Train and evaluate your ML algorithm.

Everything was clear?

Section 1. Chapter 7