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Module 2: Machine Learning for Regression — Machine Learning Zoomcamp

Lessons, materials, and key concepts for module 2 of Machine Learning Zoomcamp.

Machine Learning Zoomcamp > Module 2: Machine Learning for Regression

2. Machine Learning for Regression

• 2.1 Car price prediction project
• 2.2 Data preparation
• 2.3 Exploratory data analysis
• 2.4 Setting up the validation framework
• 2.5 Linear regression
• 2.6 Linear regression: vector form
• 2.7 Training linear regression: Normal equation
• 2.8 Baseline model for car price prediction project
• 2.9 Root mean squared error
• 2.10 Using RMSE on validation data
• 2.11 Feature engineering
• 2.12 Categorical variables
• 2.13 Regularization
• 2.14 Tuning the model
• 2.15 Using the model
• 2.16 Car price prediction project summary
• 2.17 Explore more
• 2.18 H

Lessons

Key concepts

• Regularization
• Linear Regression
• Classification Metrics
• Pandas
• Jupyter Notebooks
• scikit-learn

Homework and deadlines live in the course repository: machine-learning-zoomcamp.

Other modules in this course

• Module 1: Introduction to Machine Learning
• Module 3: Machine Learning for Classification
• Module 4: Evaluation Metrics for Classification
• Module 5: Deploying Machine Learning Models
• Module 6: Decision Trees and Ensemble Learning
• Module 8: Neural Networks and Deep Learning
• Module 9: Serverless Deep Learning
• Module 10: Kubernetes and TensorFlow Serving