Master the concepts in Machine Learning Tutorial Python - 11 Random Forest presented by codebasics. The total lesson runtime is 12:48 minutes providing step-by-step visual instructions. Follow along to build your skills on any desktop PC, Mac, tablet, or smartphone.
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Course Description & Lesson Notes
Official Video Description:
Random forest is a popular regression and classification algorithm. In this tutorial we will see how it works for classification problem in machine learning. It uses decision tree underneath and forms multiple trees and eventually takes majority vote out of it. We will go over some theory first and then solve digits classification problem using sklearn RandomForestClassifier. In the end we have an exercise for you to solve.
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Code: https://github.com/codebasics/py/blob/master/ML/11_random_forest/11_random_forest.ipynb
Exercise: Exercise description is avialable in above notebook towards the end
Exercise solution: https://github.com/codebasics/py/blob/master/ML/11_random_forest/Exercise/random_forest_exercise.ipynb
Topics that are covered in this Video:
0:00 Random forest algorithm
0:50 How to build multiple decision trees based on single data set?
2:34 Use of sklearn digits data set to make a classification using random forest
3:04 Coding (Start) (Use sklearn digits dataset for classification using random forest)
7:10 sklearn.ensemble RandomForestClassifier
10:36 Confusion Matrix (sklearn.metrics confusion_matrix)
12:04 Exercise (Classify iris flower using sklearn iris flower dataset and random forest classifier)
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π Lesson Overview & Learning Outcomes:
Welcome to the step-by-step video guide for Machine Learning Tutorial Python - 11 Random Forest taught by codebasics. This tutorial provides a comprehensive walkthrough designed to take you from foundational principles to practical implementation.
π‘ Key Topics Covered in This Course:
- Core Fundamentals & Setup: Understanding the workspace, essential tools, and initial setup for Machine Learning Tutorial Python - 11 Random Forest.
- Step-by-Step Practical Demonstration: Hands-on implementation guided by codebasics with real-world examples.
- Best Practices & Key Shortcuts: Time-saving workflows, keyboard shortcuts, and industry-standard recommendations.
- Troubleshooting & Common Pitfalls: How to avoid common beginner errors and optimize your workflow for peak efficiency.
π Recommended Prerequisites & Study Notes:
No prior advanced experience is required. Follow along with the video player above on any desktop computer, tablet, or mobile device. Pause and rewind at key steps to practice along with the instructor.
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