ai learning

Question 1

● Machine learning

Answer 1

The use of computers to identify patterns in data and make decisions based on this data

Question 2

● Deep Learning

Answer 2

A subset of machine learning that aims to create algorithms that mimic how the human brain works by learning from incredibly large data sets

Question 3

● Supervised learning

Answer 3

The task of learning a function that maps an input to an output based on previous data sets with labelled input-output combinations.

Question 4

● Unsupervised learning

Answer 4

: Algorithms that find patterns in unlabelled data where no previous patterns have been found. They do this by looking for connections or patterns in the data set.

Question 5

● Semi-Supervised learning

Answer 5

Algorithms that use a combination of labelled and unlabelled data Used because labelling large data sets can be too expensive or time consuming. Uses the labelled data sets to “learn” how to treat unlabelled data

Question 6

● Reinforcement learning

Answer 6

:algorithms that learn by interacting with the environment and using a system of “reward and punishment” to determine a best possible course of action This is the process used in the development of self driving cars

Question 7

● Data Quality

Answer 7

Poor data quality can lead to inaccurate outputs. When pre-processing data you should aim to remove all missing values

Question 8

Ai

Answer 8

artificial intelligence can be defined as the science and engineering of making intelligent computer programs capable of performing task that require subleties of judgement, interpretation and generalisation that we associate with uman intelligence.

Question 9

narrow ai

Answer 9

refers to ai systems built to perform a single task but without any skill that can be transferred to other tasks

Question 10

Artificial general intelligence

Answer 10

refers to ai systems that can autonomously solve a variety of complex problems in a variety of different domains and learn and adapt autonomously