From the course: Machine Learning and AI Foundations: Value Estimations
Join today to access over 22,600 courses taught by industry experts or purchase this course individually.
Wrap-up
From the course: Machine Learning and AI Foundations: Value Estimations
Wrap-up
- [Adam] I encourage you to try out the concepts we covered with your own data. After that, you can try experimenting with different machine learning algorithms beyond the gradient boosting algorithm we used in this course. Another popular algorithm you can experiment with in scikit-learn is the support vector regressor. If you are putting machine learning to use to solve a large-scale problem, you can try out the xgboost library. Xgboost is an add-on library for Python and several other programming languages that provides a fast implementation of gradient boosting that can be distributed across multiple computers. Finally, all of the basic concepts in this course apply to any machine learning library or toolkit no matter which programming language you use. Cloud service providers like Amazon AWS and Microsoft Azure now provide machine learning tools that let you build models in the cloud. Thanks for watching. Feel free to connect with me online.
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.