Udemy – Decision Trees, Random Forests, AdaBoost & XGBoost in Python 2019-2

Description

Decision Trees, Random Forests, AdaBoost & XGBoost in Python is the name of a Udemy training course for learning decision trees using Python. By the end of this course you will be able to identify business problems using Decision tree / Random Forest / XGBoost in machine learning, have a good understanding of advanced decision trees such as Random Forest, Bagging, AdaBoost and XGBoost. You will also be able to build and analyze a decision tree model in Python, and eventually with this course you will be able to understand machine learning concepts, practice them, and also discuss these concepts.

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

Proper understanding of the decision tree

Understand business scenarios where the decision tree is applicable.

Set up hyperparameters for a machine learning model and increase its efficiency

Use Pandas DataFrames to manipulate data and perform statistical calculations

Use the decision tree to make predictions

Learn the advantages and disadvantages of different algorithms

Course information

Publisher: Udemy Instructor: Start-Tech Academy English language Level of training: basic to advanced Number of courses: 61 Duration: 7 hours and 8 minutes

Prerequisite

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

Installation

After Extract, watch with your favorite Player.

English subtitle

Quality: 720