Day 2 AM Session Plan

This session introduces students to using the random forest model with python

Presentation Slides

Session Introduction

TEACHER LED


    What Are We Doing?

    Learning about Algorithm Types
    Splitting and Training Data
    Training and Evaluating the Random Forest Model

Supervised Learning Algorithms

TEACHER LED


    Students will learn:

    Types of machine learning algorithms
    Structure of the random forest algorithm

Random Forest for Regression

SELF-PACED


    Students will learn:

    Creating a new project
    Splitting the data into features and labels
    Scaling features using data normalization
    Training the algorithm using sklearn
    Using math to evaluate the accuracy of the regression algorithm
  • The students can continue changing the parameters for the algorithm and see how it alters the results.