Module 1 Flashcards
What is Machine Learning?
The art and science of giving computers the ability to learn to make decisions from data
What is Supervised Learning?
Uses labeled data
What is Unsupervised Learning?
Uses unlabeled data
Example of Unsupervised Learning?
Grouping customers into distinct categories
What is Reinforcement Learning?
Software agents interact with an environment
- Learn how to optimize their behaviour
- Given a system of rewards and punishments
- Draws inpiration from behavioural psychology
Applications of reinforcement learning?
Economics
Genetics
Game Playing
Classification?
Target variable consists of categories
Regression?
Target variable is continuous
Example of Supervised learning?
Doctor’s diagnosis
EDA?
Exploratory Data Analysis
Most commonly used metric in classification?
Accuracy - fraction of correct predictions
Larger K?
Smoother decision boundary - less complex model
Smaller K?
More complex model - can lead to overfitting
Several characteristics of Machine Learning?
Main Branches of Machine Learning
Model Creation Process
Model Characteristics
Main Branches of Machine Learning?
Supervised
Unsupervised
Semi-Supervised
Reinforcement Learning
