Sources of Data Flashcards

1
Q

What are three Data Sources

A

Internal Data, Existing external data, Proprietary collection

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2
Q

What is Internal Data

A

Data from within the company/institution

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3
Q

What is Existing external data

A

From internal data of third parties, maybe free maybe not, collected and ready to use

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4
Q

What is Proprietary collection

A

Provided by third parties but requiring effort to go out and collect or process

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5
Q

Define API

A

Application Programming Interface

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6
Q

What are types of way data is collected

A

Some host datasets for download as hosted files (CVS, text files, directories of images etc), some may have an API which allows interacting with their information/services through a pre-defined functionality (these often cost to access), Web scraping (obtaining public facing information from websites), they may have restrictions on usage

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7
Q

What are the four dimensionality of a table

A

Scalar, Vector, Matrix, Tensor

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8
Q

Define Scalar

A

Singular numerical value, scalar in italics and lowercase

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9
Q

Define Vector

A

1D structure of values, vector in bold and lowercase

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10
Q

Define Matrix

A

2D Structure of values, matrix in bold and uppercase

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11
Q

Define Tensor

A

N-D structure of values, tensor in bold and uppercase

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12
Q

What is a formal way to describe these structures with their shape

A

e.g. 1x3, 3x2, 1x2x3, can combine this with a way to describe their content,

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13
Q

How do you represent categories of numbers

A

Use symbols to represent categories (Whole, Natural, Integer, Real, …) and use superscripts to describe size

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14
Q

Is NumPy “row-major” or “column-major”

A

NumPy is row-major

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15
Q

What does X[0,1] access in Numpy

A

It accesses the top right element, which is located in row 0 and column 1

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16
Q

What is the name for the position X[0,1] in matrix X

A

X01, 01 is subscripts

17
Q

How is indexing into array structures shown

A

Indexing into array structures is shown with subscripts of the lowercase of the symbol for the structure

18
Q

What does X01(subscript) mean in NumPy indexing

A

X01(subscript) means to get everything within row 0 and column 1 in NumPy indexing

19
Q

How is the ith sample indexed in NumPy

A

The ith sample is indexed with x in Numpy

20
Q

How are all observations for feature j indexed in NumPy

A

All observations for feature j are indexed with x*j in NumPy

21
Q

How do we get xj in NumPy

A

We can get xj in NumPy using X[i,:] or X[i]

22
Q

How do we get x*j in NumPy

A

We can get x*j in NumPy using X[:,j]