Chapter 13. When your data science project fails
This chapter covers
- Why data science projects tend to fail
- What you can do when your project fails
- How to handle the negative emotions from failure
Most data science projects are high-risk ventures. You’re trying to predict something no one has predicted before, optimize something no one has optimized before, or understand data that no one has looked at before. No matter what you’re doing, you’re the first person doing it; the work is almost always exploratory. Because data scientists are continuously doing new things, you will inevitably hit a point where you find out that what you hoped for ...
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