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  1. Learn the most important language for data science.

  2. Refresh. Practical data skills you can apply immediately: that's what you'll learn in these no-cost courses. They're the fastest (and most fun) way to become a data scientist or improve your current skills.

  3. Kaggle Notebooks are a computational environment that enables reproducible and collaborative analysis.

  4. Learn how to build your first machine learning model, a decision tree classifier, with the Python scikit-learn package, submit it to Kaggle and see how it performs! Hugo Bowne-Anderson 11 min

  5. Kaggle Notebooks are a computational environment that enables reproducible and collaborative analysis.

  6. Mar 10, 2017 · Overview. I recommend a simple 4-step process. The steps are: Pick a platform. Practice on standard datasets. Practice old Kaggle problems. Compete on Kaggle. The process is easy to describe, but difficult to implement. It is going to take time and effort. It is going to be hard work. But…

  7. Learn how to build your first machine learning model, a decision tree classifier, with the Python scikit-learn package, submit it to Kaggle and see how it performs!

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