1. Introduction to Machine Learning with scikit-learn

    Buy now Learn more
  2. Introduction

    1. Welcome to the course!
    2. Download the course notebooks
  3. 1. What is Machine Learning, and how does it work?

    1. Lesson 1
    2. Quiz 1
  4. 2. Setting up Python for Machine Learning: scikit-learn and Jupyter Notebook

    1. Lesson 2
    2. Quiz 2
  5. 3. Getting started in scikit-learn with the famous iris dataset

    1. Lesson 3
    2. Quiz 3
  6. 4. Training a Machine Learning model with scikit-learn

    1. Lesson 4
    2. Quiz 4
  7. 5. Comparing Machine Learning models in scikit-learn

    1. Lesson 5
    2. Quiz 5
  8. 6. Data science pipeline: pandas, seaborn, scikit-learn

    1. Lesson 6
    2. Quiz 6
  9. 7. Cross-validation for parameter tuning, model selection, and feature selection

    1. Lesson 7
    2. Quiz 7
  10. 8. Efficiently searching for optimal tuning parameters

    1. Lesson 8
    2. Quiz 8
  11. 9. Evaluating a classification model

    1. Lesson 9
    2. Quiz 9
  12. 10. Building a Machine Learning workflow

    1. Lesson 10
    2. Quiz 10
  13. Conclusion

    1. Request your certificate of completion
    2. Take another course from Data School!
  1. Products
  2. Course
  3. Section

Conclusion

  1. Introduction to Machine Learning with scikit-learn

    Buy now Learn more
  2. Introduction

    1. Welcome to the course!
    2. Download the course notebooks
  3. 1. What is Machine Learning, and how does it work?

    1. Lesson 1
    2. Quiz 1
  4. 2. Setting up Python for Machine Learning: scikit-learn and Jupyter Notebook

    1. Lesson 2
    2. Quiz 2
  5. 3. Getting started in scikit-learn with the famous iris dataset

    1. Lesson 3
    2. Quiz 3
  6. 4. Training a Machine Learning model with scikit-learn

    1. Lesson 4
    2. Quiz 4
  7. 5. Comparing Machine Learning models in scikit-learn

    1. Lesson 5
    2. Quiz 5
  8. 6. Data science pipeline: pandas, seaborn, scikit-learn

    1. Lesson 6
    2. Quiz 6
  9. 7. Cross-validation for parameter tuning, model selection, and feature selection

    1. Lesson 7
    2. Quiz 7
  10. 8. Efficiently searching for optimal tuning parameters

    1. Lesson 8
    2. Quiz 8
  11. 9. Evaluating a classification model

    1. Lesson 9
    2. Quiz 9
  12. 10. Building a Machine Learning workflow

    1. Lesson 10
    2. Quiz 10
  13. Conclusion

    1. Request your certificate of completion
    2. Take another course from Data School!
2 Lessons
    1. Request your certificate of completion
    2. Take another course from Data School!
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