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day12-xgboost's Introduction

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Pre-Read

  1. XGBoost Documentation
  2. Complete Guide to Parameter Tuning in XGBoost

Learning Objectives

  1. Learn what Boosting is and how use it in ML
  2. Learn what Gradient Boosting Machines are and how to use them to build ML models
  3. Learn to configure GBM using early-stopping and hyperparameter tuning to achieve superior performance
  4. Learn how to interpret XGBoost models

Hands-on Skills

  1. Implementation of GBM using sklearn library
  2. Building, Saving and Reloading models using XGBoost library
  3. Implementing Early-stopping and Hyperparameter tuning
  4. Interpreting and visualizing XGBoost models

Slides

@gslides

Notebooks

To be updated

Assignments

To be updated

Post Reads

  1. XGBoost: A Scalable Tree Boosting System
  2. Gradient Boosting

day12-xgboost's People

Contributors

gyandhanee avatar

Watchers

Soumendra Prasad Dhanee avatar James Cloos avatar Suraj Jadhav avatar PradeepJaiswar avatar Mayuresh Suresh Shilotri avatar Mudassir Khan avatar Sangam Angre avatar Shweta Doshi avatar

Forkers

ameya-s

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