Description
Decision Trees, Random Forests, AdaBoost & XGBoost in Python is the name of a Udemy training course for learning decision trees using the Python language. After completing this course, you will be able to determine business problems using Decision tree/Random Forest/XGBoost in machine learning, have a proper understanding of advanced decision trees such as Random Forest, Bagging, AdaBoost and XGBoost. Also, you will be able to build a decision tree model in Python and analyze it, and finally with this course you will be able to understand the concepts of machine learning, practice them and also discuss these concepts.
Features of the Decision Trees, Random Forests, AdaBoost & XGBoost in Python course:
- Proper understanding of decision trees
- Understand the business scenarios where the decision tree is applicable.
- Adjusting the hyperparameters of a machine learning model and increasing its efficiency
- Using Pandas DataFrames to manipulate data and perform statistical calculations
- Use a decision tree to make predictions
- Learning the advantages and disadvantages of different algorithms
Course details:
Publisher: Udemy
teacher: Start-Tech Academy
English language
Training level: introductory to advanced
Number of courses: 61
Duration: 7 hours and 8 minutes
Course topics on 11-2020:
Course prerequisites:
Students will need to install Python and Anaconda software, but we have a separate lecture to help you install the same
Pictures
Sample video
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720
download link
Password file(s): www.downloadly.ir
Size
1.9 GB
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