Courses Quizzes Blog Events Knowledge

Lesson 5 - Gradient Boosting with XGBoost

Machine Learning with Python: Zero to GBMs

Lesson 1 - Linear Regression with Scikit Learn Lesson 2 - Logistic Regression for Classification Assignment 1 - Train Your First ML Model Lesson 3 - Decision Trees and Hyperparameters Lesson 4 - Random Forests and Regularization Assignment 2 - Decision Trees and Random Forests

Course Project - Real-World Machine Learning Model Lesson 6 - Unsupervised Learning and Recommendations

The following topics are covered in this lesson:

Downloading a real-world dataset from a Kaggle competition
Performing feature engineering and prepare the dataset for training
Training and interpreting a gradient boosting model using XGBoost
Training with KFold cross-validation and ensembling results
Configuring the gradient boosting model and tuning hyperparameters

Please provide your valuable feedback on this link to help us improve the course experience.

Ask questions and get help on the discussion forum.

Attend weekly study hours on the Jovian Discord Server

aakashns/python-gradient-boosting-machines

Run Locally (Clone)

Code it Yourself

Loading...