Gradient Boosting Courses and Certifications

Introduction to Machine Learning with Gradient Boosting Models

Master gradient boosting models through hands-on practice with Tesla stock predictions, covering model training, cross-validation, hyperparameter tuning, feature importance analysis, and early stopping techniques.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Foundations of Gradient Boosting

Master gradient boosting by building decision trees, creating ensembles, and understanding feature importance through hands-on banking data analysis and model optimization.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Conf42

Stop Failures Before They Happen - Gradient Boosting for Workflow Risk Prediction

Discover how to predict and prevent workflow failures using gradient boosting with CatBoost, SHAP explanations, and Prefect for early signal detection in ML pipelines.

• YouTube
• 16 minutes
• Self-Paced
• Free Video

LightGBM Made Simple

Master LightGBM's leaf-wise architecture, histogram algorithms, and parameter optimization through hands-on experiments comparing performance against traditional boosting methods.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Career Certificate

Mastering Gradient Boosting with XGBoost & LightGBM

Master gradient boosting techniques using XGBoost, LightGBM, and CatBoost to build, tune, and interpret powerful models for real-world classification problems with hands-on practice.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate
• 3 courses

Extreme Gradient Boosting with XGBoost

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

EuroPython Conference

CatBoost - The New Generation of Gradient Boosting

Explore CatBoost, a powerful gradient boosting library for machine learning. Learn its advantages, applications, and unique features for handling categorical data and achieving state-of-the-art results.

• YouTube
• 42 minutes
• Self-Paced
• Conference Talk

Credit Risk Modeling in Python

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Tree-Based Models in R

In this course, you'll learn how to use tree-based models and ensembles for regression and classification.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Hyperparameter Tuning in R

Learn how to tune your model's hyperparameters to get the best predictive results.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

EuroPython Conference

Histogram-based Gradient Boosting in scikit-learn 0.21

Explore the new Histogram-based Gradient Boosting implementation in scikit-learn 0.21, offering competitive performance with XGBoost and LightGBM for efficient machine learning on tabular data.

• YouTube
• 45 minutes
• Self-Paced
• Conference Talk

Career Certificate

Intro to Machine Learning in Trading with $TSLA

212 ratings at CodeSignal

Dive into financial data analysis and machine learning techniques using Tesla stock data to build predictive trading models and make data-driven investment decisions.

• CodeSignal
• 6 hours
• Self-Paced
• Free Certificate
• 4 courses

Intro to Model Optimization in Machine Learning

Master machine learning optimization techniques using real medical data, from hyperparameter tuning to advanced ensemble methods, enhancing your ability to build accurate predictive models.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

Ensemble Methods from Scratch

Master ensemble methods by building Bagging, Random Forest, AdaBoost, and Gradient Boosting implementations from scratch. Learn to enhance predictive models through hands-on coding without relying on libraries.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

Ensembles in Machine Learning

Master ensemble learning techniques like bagging, boosting, and stacking to enhance predictive modeling performance, from Random Forests to Gradient Boosting and AdaBoost implementations.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate