1. Introduction to Machine Learning with scikit-learn

    • Buy now
    • Learn more
  2. Introduction

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

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

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

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

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

    • Lesson 5
    • Quiz 5
  8. Intermission

    • Can I ask you a quick favor?
  9. 6. Data science pipeline: pandas, seaborn, scikit-learn

    • Lesson 6
    • Quiz 6
  10. 7. Cross-validation for parameter tuning, model selection, and feature selection

    • Lesson 7
    • Quiz 7
  11. 8. Efficiently searching for optimal tuning parameters

    • Lesson 8
    • Quiz 8
  12. 9. Evaluating a classification model

    • Lesson 9
    • Quiz 9
  13. 10. Building a Machine Learning workflow

    • Lesson 10
    • Quiz 10
  14. Conclusion

    • Can I ask you a quick favor?
    • Request your certificate of completion
    • Take another course from Data School!
    • Earn money by promoting Data School's courses!
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  2. Course
  3. Section

Introduction

  1. Introduction to Machine Learning with scikit-learn

    • Buy now
    • Learn more
  2. Introduction

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

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

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

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

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

    • Lesson 5
    • Quiz 5
  8. Intermission

    • Can I ask you a quick favor?
  9. 6. Data science pipeline: pandas, seaborn, scikit-learn

    • Lesson 6
    • Quiz 6
  10. 7. Cross-validation for parameter tuning, model selection, and feature selection

    • Lesson 7
    • Quiz 7
  11. 8. Efficiently searching for optimal tuning parameters

    • Lesson 8
    • Quiz 8
  12. 9. Evaluating a classification model

    • Lesson 9
    • Quiz 9
  13. 10. Building a Machine Learning workflow

    • Lesson 10
    • Quiz 10
  14. Conclusion

    • Can I ask you a quick favor?
    • Request your certificate of completion
    • Take another course from Data School!
    • Earn money by promoting Data School's courses!

2 Lessons
    • Welcome to the course!
    • Download the course notebooks