Overview
Join over 9 million learners and start Extreme Gradient Boosting with XGBoost today!
Do you know the basics of supervised learning and want to use state-of-the-art models on real-world datasets? Gradient boosting is currently one of the most popular techniques for efficient modeling of tabular datasets of all sizes. XGboost is a very fast, scalable implementation of gradient boosting, with models using XGBoost regularly winning online data science competitions and being used at scale across different industries. In this Extreme Gradient Boosting with XGBoost course at Data Camp, you'll learn how to use this powerful library alongside pandas and scikit-learn to build and tune supervised learning models. You'll work with real-world datasets to solve classification and regression problems.
Programme Structure
Chapters include:
- Classification with XGBoost
- Fine-tuning your XGBoost model
- Regression with XGBoost
- Using XGBoost in pipelines
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
Disciplines
Information Technology (IT) Data Science & Big Data Machine Learning View 592 other Short Courses in Data Science & Big Data in United StatesAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Prerequisites
- Supervised Learning with scikit-learn
- Case Study: School Budgeting with Machine Learning in Python
Tuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
Basic Access: Free; Premium (for individuals): $12.42 per month billed annually; Teams: $25 per month billed annually; Enterprise: Contact sales for pricing