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Introduction to Machine Learning with caret

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Overview

Embark on your data science journey with the introduction to machine learning using the caret package in R. This course guides you through essential steps like data preprocessing, splitting datasets, training simple models, and evaluating their basic performance.

Syllabus

Unit 1: Data Preprocessing

Apply Log Transformation to Data
Fix the Data Preprocessing Code
Preprocess the Iris Dataset
Preprocessing with Transformations
Data Preparation in R

Unit 2: Splitting the Dataset

Adjust the Data Split Ratio
Fix the Data Split Issue
Dataset Splitting Practice
Splitting Iris Dataset Practice
Splitting Dataset from Scratch

Unit 3: Training a Simple Model

Switching to Decision Trees
Fix the SVM Model Code
Fill in the Missing Pieces
Train SVM with Key Predictors
Training a Linear SVM Model

Unit 4: Model Prediction and Evaluation

Evaluate Performance with a New Model
Fix Prediction and Evaluation Code
Evaluate Model Predictions with R
Evaluate SVM Model Predictions for iris
Model Prediction and Evaluation

Unit 5: Cross-Validation

Change Model and Cross-Validation
Find and Fix Code Mistakes
Defining Cross-Validation Parameters
Cross-Validation in Action
Cross-Validation Mastery Test

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