Introduction to Machine Learning with caret

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.

Lessons and practices

Lesson 1: Data Preprocessing

Apply Log Transformation to Data

Fix the Data Preprocessing Code

Preprocess the Iris Dataset

Preprocessing with Transformations

Data Preparation in R

Lesson 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

Lesson 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

Lesson 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

Lesson 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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