In this project, you’ll assume the role of a data scientist tasked with predicting the extent of damage caused by forest fires. Using a real-world dataset, you’ll apply advanced machine learning techniques in Python to build and optimize linear regression models.
Throughout the project, you’ll employ crucial skills such as data cleaning, exploratory analysis, feature engineering, cross-validation, and regularization. By iterating on a reference model, you’ll learn how to systematically enhance model performance. This hands-on experience will strengthen your machine learning expertise and demonstrate your ability to tackle complex, real-world prediction problems.
Objective: Develop an optimized machine learning model to accurately predict forest fire damage, showcasing your proficiency in applying advanced techniques for model improvement.
Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.
Build confidence with our in-depth projects, and show off your data skills.
Work with real data from day one with interactive lessons and hands-on exercises.
Share the evidence of your hard work with your network and potential employers.
Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.
We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.
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