big data

Question 1

big datach characteristics

Answer 1

1. Volume (megabites;terabites itp.)
2. Variety (photo, audio ,text)
3. Velocity (kwartalne, itp)

Question 1

machine learning

Answer 1

ability of the algorithm to generate structure or predictions without any help from a human.

algorithms aim to “find the pattern, apply the pattern.”

Question 2

neural networks

Answer 2

A type of computer program design based on how the human brain learns and processes information.

Question 3

expert system

Answer 3

A type of computer programming, often based on “if–then” rules

Question 4

overfitting

Answer 4

ML model learns the input and target dataset too precisely, making the system more likely to discover false relationships or unsubstantiated patterns that will lead to prediction errors.

Question 5

underfitted

Answer 5

When a machine learning model treats true parameters as if they are noise and is unable to recognize relationships

Question 6

supervised learning

Answer 6

learning based on labeled training data. In supervised learning, inputs and outputs are labeled, or identified, for the algorithm.

Question 7

unsupervised learning

Answer 7

computers are not given labeled data but instead are given only data from which the algorithm seeks to describe the data and their structure

Question 8

deep learning

Answer 8

An area of AI in which a system uses neural networks to perform multistage, non-linear data processing to identify patterns

Question 9

data science

Answer 9

interdisciplinary field that harnesses advances in computer science, statistics, and other disciplines for the purpose of extracting information from big data

Question 10

Natural language processing (NLP)

Answer 10

A field of research within the field of text analytics and at the intersection of computer science, AI, and linguistics that focuses on developing computer programs to analyze and interpret human language.

Question 11

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