In this video, learn the tools that allow you to handle a lot of common challenges in machine learning, as well as what those challenges are.
- [Instructor] Now that we've set the stage…what machine learning is, what it is not,…and we've discussed a few examples…of what machine learning looks like in everyday life,…let's talk about some common challenges we run into…with machine learning before we start diving into code…in the next chapter.…Let's first take a quick look at the slide…that we saw back in lesson two…where we talked about questions you should ask…to determine if machine learning is a reasonable choice…to solve your given problem.…I bring this up because common challenges…in machine learning flows pretty directly…from these questions.…
So, in thinking about common challenges we run into…with machine learning, they tend to fall into four…high-level categories.…Problem scoping, data, infrastructure, and latency.…We'll walk through these high-level groups one by one,…and I should clarify that these aren't necessarily blockers…so much as they are just simply things…to look out for when you're trying…to solve a problem using machine learning.…
Author
Released
5/10/2019- What is machine learning (ML)?
- ML vs. deep learning vs. AI
- Handling common challenges in ML
- Plotting continuous features
- Continuous and categorical data cleaning
- Measuring success
- Overfitting and underfitting
- Tuning hyperparameters
- Evaluating a model
Skill Level Beginner
Duration
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Conclusion
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Next steps1m 23s
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Video: Common challenges