Decision Trees, Random Forests, AdaBoost & XGBoost in Python – Free Udemy Courses

Free Certification Course Title: Decision Trees, Random Forests, AdaBoost & XGBoost in Python

Decision Trees and Ensembling techniques in Python. How to run Bagging, Random Forest, GBM, AdaBoost & XGBoost in Python.

Decision Trees, Random Forests, AdaBoost & XGBoost in Python
Decision Trees, Random Forests, AdaBoost & XGBoost in Python


  • Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same.

What you’ll learn:

  • Get a solid understanding of the decision tree.
  • Understand the business scenarios where the decision tree is applicable.
  • Tune a machine learning model’s hyperparameters and evaluate its performance.
  • Use Pandas DataFrames to manipulate data and make statistical computations.
  • Use decision trees to make predictions.
  • Learn the advantage and disadvantages of the different algorithms.

Course Content:



Who this course is for:

  • People pursuing a career in data science.
  • Working Professionals beginning their Data journey.
  • Statisticians needing more practical experience.
  • Anyone curious to master Decision Tree technique from Beginner to Advanced in a short span of time.

This course includes:

  • 7 hours of on-demand video.
  • 3 articles.
  • 19 downloadable resources.
  • Full lifetime access.
  • Access on mobile and TV.
  • Certificate of Completion.

Created by Start-Tech Academy


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