big data Flashcards

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1
Q

big datach characteristics

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

machine learning

A

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

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

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2
Q

neural networks

A

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

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3
Q

expert system

A

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

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4
Q

overfitting

A

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.

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5
Q

underfitted

A

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

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6
Q

supervised learning

A

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

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7
Q

unsupervised learning

A

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

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8
Q

deep learning

A

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

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9
Q

data science

A

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

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10
Q

Natural language processing (NLP)

A

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.

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11
Q

algoritm trading

A
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