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

    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.

    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 different algorithms.

    Requirements:

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

    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

    How to Subscribe For Decision Trees, Random Forests, AdaBoost & XGBoost in Python?

    1. Sign Up on Udemy.com
    2. Subscribe Here(Decision Trees, Random Forests, AdaBoost & XGBoost in Python): Click Here

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