Introduction

Question 1

What is the similarity and difference between linear regression and classification?

Answer 1

Both models are used to predict future data

Linear regression predicts a future ‘value’
E.g. housing ‘prize’ (numerical and continuous)

Classification predicts a category

Question 2

What is the similarity and difference between clustering and classification?

Answer 2

Both predict categories

Classification is if you know what outcome you’re looking for

Clustering is if you don’t know what you’re looking for…
It finds new patterns, trends and groupings in data

Question 3

What is association rule learning?

Answer 3

It finds features that tend to occur together

E.g. people who bought x also bought y

Question 4

What’s the difference between prediction models and reinforcement learning?

Answer 4

Reinforcement learning is to get AI to make ‘Decisions’ based on inputted data

I.e. Model looks at data that occurs at time T to make decision which occurs at time T+1

It learns what decisions to make via reward and punishment

Question 5

What is natural language processing?

Answer 5

It’s when machine learning is applied to text and language (speech).

Question 6

What’s the difference between previously mentioned prediction models (regression & classification) and deep learning?

Answer 6

Regression models only predict continuous numerical values

Classification models only predict category

Deep learning can be used to predict:

• Continuous numbers
• Binary (e.g. Yes/No)
• Categorical data