24
Getting started with Anaconda Notebooks
Course Overview and Introduction
What is Machine Learning?
Machine Learning Exercise: Inputs and Outputs
Machine Learning vs. Traditional Programming
CRISP-DM Framework
Problem Framing for Lab: Predict Home Values
Model Performance Measures
Lab Overview
Exploratory Data Analysis and Preparation
Exploratory Data Analysis and Preparation Continued
Feature Engineering
Data Cleaning
Feature Scaling
Model Training and Evaluation
Model Selection
Hyperparameter Optimization
Model Development
Evaluation Using Cross-validation
Hyperparameter Optimization Techniques
Test Set Evaluation
Considerations for MLOps
Summary and ML Model Exercises
End of course survey
img