Ensemble machine learning in Python : Random Forest, AdaBoost.

Format:

Video

Contributor:

Lazy Programmer, instructor.

Packt Publishing, publisher.

Language:

English

Subjects (All):

Machine learning.

Python (Computer program language).

Physical Description:

1 online resource (1 video file (3 hr., 2 min.)) : sound, color.

Edition:

[First edition].

Place of Publication:

[Birmingham, United Kingdom] : Packt Publishing, 2026.

Summary:

In this 3-hour course, you will master ensemble machine learning techniques like Random Forest and AdaBoost to enhance model performance. Learn how to combine multiple models to improve prediction accuracy and tackle complex tasks using hands-on coding examples. What I will be able to do after this course Understand key concepts of ensemble learning and model optimization Implement Random Forest and AdaBoost algorithms for classification and regression Optimize model performance using techniques like bagging and boosting Apply ensemble learning techniques to real-world datasets and problems Course Instructor(s) The course is taught by Lazy Programmer, a skilled educator with a decade of experience in machine learning, deep learning, and statistics. He has authored pioneering courses and helped thousands of students master data science and AI. Who is it for? This course is ideal for intermediate learners, data scientists, machine learning engineers, and Python programmers. It's designed for those with basic knowledge of regression, classification models, and decision trees.

Notes:

OCLC-licensed vendor bibliographic record.

ISBN:

9781807785437

OCLC:

1587232399