chapter 1 Flashcards

1
Q

_____ refers to the simulation of human intelligence by intelligent agents, either physical or software, that is taught to think and behave like people.

A

Artificial intelligence (AI)

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2
Q

Artificial intelligence is a broad field in which computers to solve problems by simulating complex biological processes such as

A

learning, reasoning, and self-correction.

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3
Q

It is the subfield of AI that is employed in a variety of applications such as learning current events, formulating solutions for existing problems and recommend for future events, and classifying similar ones to make day-to-day life easier.

A

Machine learning

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4
Q

machine learning can be either ___ or ____

A

predictive or descriptive

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5
Q

A technology that is used to train machines to perform various actions such as predictions, recommendations and estimations, etc., based on

A

historical data or past experience.

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6
Q

A technique which enables a machine to mimic human behaviors

A

AI

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7
Q

uses statistical methods to enable machine to improve with experiences

A

ML

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8
Q

which computers learn from experience and comprehend the world through the use of concept hierarchy. It advances to solve problems involving unstructured data sets such as images, video, and free text.

A

Deep learning

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9
Q

ML working procedure

A
  1. data acquisition and understanding
  2. data cleaning
  3. modeling
  4. deployment
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10
Q

Types of Machine learning: Based on input data

A

supervised, unsupervised and reinforcement

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11
Q

an algorithm to accurately assign test data into specific categories. It recognizes specific entities within the dataset and attempts to draw some conclusions on how those entities should be labeled or defined

A

classification

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12
Q

ML classification

A

binary, multi-class and multi label classification

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13
Q

an algorithms predict the output values based on input features from the data fed in the system.

A

Regression

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14
Q

Unsupervised learning models are utilized for three main tasks—

A

clustering, association, and dimensionality reduction.

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15
Q

list four Characteristics of Reinforcement Learning

A

no supervisor, sequential decision making and time play crucial rule

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16
Q

Recognition or authentication of people using their physiological and/or behavioral characteristics.

A

Biometric recognition

17
Q

____ are instances that do not obey the rule and are exceptions.

A

outlier

18
Q

a technology that uses various techniques to discover hidden information or pattern (i.e., novel, valid, understandable, and useful) from data in large databases (e.g. data warehouse).

A

data mining

19
Q

choosing of KDD data set is based on

A

quality