Practice - The Machine Learning Workflow: A Lifecycle
Practice Questions
Test your understanding with targeted questions
What is the first step in a machine learning workflow?
💡 Hint: Think about what you need to define before moving forward in a project.
Name one source from which data can be acquired.
💡 Hint: Consider sources that provide data without needing extensive permissions.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does the term 'data preprocessing' refer to in machine learning?
💡 Hint: Consider what has to happen before you train a model.
True or False: The initial problem definition in a machine learning workflow can be altered later without consequences.
💡 Hint: Reflect on how foundational decisions influence a project.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Evaluate a scenario where a company aims to predict sales for the next quarter. Discuss the potential pitfalls of neglecting the problem definition stage before collecting data.
💡 Hint: Consider how unclear goals could steer data collection away from business objectives.
A team is analyzing data for patterns but lacks proper preprocessing. What challenges might arise, and how could these challenges affect model outcomes?
💡 Hint: Think about how data quality directly influences model training.
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Reference links
Supplementary resources to enhance your learning experience.
- Introduction to Machine Learning
- Machine Learning Workflows
- Data Preprocessing in Python
- Exploratory Data Analysis with Python
- Feature Engineering with Python
- Replace Missing Values with Python
- Hyperparameter Tuning in Machine Learning
- Machine Learning Model Deployment
- Basics of Data Visualization for Exploratory Data Analysis