Data Tools · Module 4
The scikit-learn API3 lessons and their Study toolkit.
Watch each lesson, answer its quiz, then do its practice. After the last lesson: the module quiz, the project, and the interview questions.
3of 3 lessons ready
23quiz questions
0key terms
3self-checking notebooks
The lessonsin the order to take them.
3 lessons ready to study
- 4.1Meet scikit-learnSay what scikit-learn is for, and fit and score a first model against a baseline. Open
- 4.2Estimators: fit, predict, transformUse any scikit-learn estimator with the same verbs, and tell what you set before `fit` from what it learned during it. Open
- 4.3Pipelines, and Where scikit-learn Goes NextChain a transformer and a model into one object, score it with one line of cross-validation, and know which ML video takes each topic further. Open
Module quiz11 questions across it all.
Take it after the last lesson. Your first pick on each question is the one that counts.
Practicebuild it without a template.
Stated as a problem, with no step-by-step instructions. Working out the steps is the point.
Notebooksthat check your answers.
Open them in Google Colab. Each answer is checked as you go: correct, wrong with the expected value, or not answered yet.
- Baselines and estimatorsLessons 4.1 and 4.2 Courses plan
- Pipelines and validationLessons 4.3 Courses plan
- First model comparisonThe module project, with checks Courses plan
Common mistakesacross the whole module.
What you see when it goes wrong, why it happens, and the fix.
Referencefor revising and for interviews.
The cheat sheet is one page of the module’s terms, rules and gotchas. The interview questions come with model answers.