Week 1 - Introduction

How can you derive structure in data when conducting unsupervised learning?

By clustering the data based on relationships among the variables in the data.

What are two types of unsupervised learning?

Clustering and Non-clustering

In the example of a machine learning how to be better at checkers, what would the following variables represent? E T P

E - experience - the experience of playing many games of checkers T - task - the task of playing checkers P - performance measure - the probability that the machine will win the next game

What is unsupervised learning?

allows us to approach problems with little or no idea what our results should look like. We can derive structure from data where we don't necessarily know the effect of the variables. There is no feedback based on the prediction results.

What is supervised learning?

given a data set and already know what our correct output should look like, having the idea that there is a relationship between the input and the output.

What types of questions can supervised learning consist of?

regression categorization

What are the two definitions of machine learning?

the field of study that gives computers the ability to learn without being explicitly programmed. A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.

What is a regression problem?

trying to predict results within a continuous output, meaning that we are trying to map input variables to some continuous function. In a classification problem, we are instead trying to predict results in a discrete output. In other words, we are (Standard graph with an independent and dependent variable)

What is a categorization problem?

trying to predict the classification of a result. In which group will it fall in?