From the course: Applied Machine Learning: Ensemble Learning (2022)
Join today to access over 24,700 courses taught by industry experts.
How to continue advancing your skills - Python Tutorial
From the course: Applied Machine Learning: Ensemble Learning (2022)
How to continue advancing your skills
- [Derek] Congratulations. You now know how three of the most powerful ensemble learning techniques are implemented, how they reduce overall error, what some of the key hyper parameters are for each, and their relative strengths and weaknesses. You're now ready to apply these techniques to new problems that you encounter. Understanding what drives each of these algorithms and how and when to use them will allow you to truly optimize a model that is tailored to the specific problem in front of you. This ability to deliver a powerful tailored solution is truly invaluable, but don't stop here. There's still so much more to learn. Here are a few next steps that you could take. First, if you want to learn more about some of the foundations of machine learning that generalize to all problems, check out one of my other courses in this series, Applied Machine Learning: Foundations. Second, we only explored ensemble learning…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.