explanation
The courses on Udemy for learning decision trees using the Python language are named Decision Trees, Random Forests, AdaBoost & XGBoost in Python. By the end of the course, you will have encountered business problems in using decision trees/Random Forest/XGBoost on machine learning sets and have a good understanding of advanced decision trees such as Random Forest, Bagger, AdaBoost, and XGBoost. mental. You will also be able to create a model decision tree in Python and analyze it. Finally, through this course, you will understand and practice the concepts of machine learning and learn about the concepts discussed. .
This course covers decision trees, random forests, AdaBoost, and XGBoost in Python.
- Proper understanding of decision trees
- Understand business scenarios where decision trees can be applied.
- Adjust hyperparameters of models and machine learning and increase performance.
- Manipulate data and perform statistical calculations using Pandas DataFrames
- Use decision trees to make predictions
- Learn about the usefulness and problems of various algorithms.
Profile Course:
Publisher: Udemy
teacher: Start Tech Academy
Language:English
Education level: Beginner to advanced
Number of courses: 61
Duration: 7 hours 8 minutes
Course content for dates 11-2020:
precondition:
Students will need to install the Python and Anaconda software, but there are separate classes available to help you install them.
image
sample video
installation manual
Extract it and watch it in your favorite player.
Subtitles: English
Quality: 720
download link
Password file: free download software
file size
1.9GB