AI glossary: terms starting with E

37 terms starting with E, each defined the way the lesson that teaches it uses it, with a link to every lesson where it appears.

e

the base whose exponential has slope one at zero, 2.71828…

Example: slope 1.0005 at step 0.001

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EDA report

Reproducible observations linked to explicit limits and next checks.

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edge case

An input at the limit of what the code handles: an empty list, one item, an empty string.

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eigendecomposition

A = QΛQᵀ: rotate, stretch along the axes, rotate back

Example: Λ = diag(1, 3)

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eigenvalue

λ, the factor it is stretched by

Example: 3

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eigenvector

a nonzero vector the matrix only stretches, Av = λv

Example: (1, 1)

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elastic net

A penalty mixing the L1 and L2 penalties.

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element

One value stored in a list.

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eligible denominator

The cases allowed into the stated rate under its selection rule: the simulated approvals.

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eligible unit

The object that can be selected once for this task; here, one invoice ID with all of its lines.

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empirical CDF

The observed fraction at or below a value. It steps up by 1 / n at each observation and is flat between them.

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Empirical cumulative distribution

observed fraction at or below each duration.

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empirical probability

Event count divided by the recorded total: 492 / 284,807 = 0.173%.

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empirical standard error

The SD of the simulated sample means: £370.99 at 25 IDs.

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empirical variance

The mean of squared distances from the empirical mean, in squared units.

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encoding

The rule that turns text into bytes, and bytes back into text. This course always uses UTF-8.

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entry

one number in a matrix, xᵢⱼ

Example: x₃₂ = 2

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epoch

One pass through every training row.

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error case

An input the code should refuse, checked by testing that it raises.

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Estimate

a value calculated from observed cases. (00.2): the rate measured in the observed period. An estimate can change when the observed cases change.

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estimator

An object that learns from data in fit and answers in predict. Every scikit-learn model is one.

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Euclidean distance

The square root of the sum of squared differences.

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Evaluation

measuring a forecast on cases excluded from its calculation.

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event

A specified set of outcomes, such as F, the 492 rows with Class = 1.

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event A

The rows satisfying a declared condition; here Amount > 100, 56,508 rows.

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evidence log

A record of each observation, a plausible alternative explanation and the next check.

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example

One item of data, with its label: a message and spam or ham.

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exception

An object Python raises when a line can not be carried out; unhandled, it stops the program.

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execution count

The order in which cells ran: the number in square brackets beside a cell, such as [3].

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expected cost

Average assigned cost under the stated outcome frequencies and cost matrix: $117.75 for PAY_0 > 0, $97.98 for PAY_0 >= 0.

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expected value

The probability-weighted average of a random variable's possible values.

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exploratory data analysis (EDA)

Inspecting recorded data, its quality and its patterns before drawing conclusions.

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exponent

the power of two the significand is multiplied by

Example: −1 for 0.75

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exponential

the input is the exponent, bˣ; each equal step multiplies the output by the same factor

Example: 2ˣ doubles at every step

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exponential function

exp(x) = eˣ

Example: np.exp(1) = 2.718281828459045

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expression

Any piece of code that Python evaluates to a value: 10 + 3, price * 2, age >= 18.

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extrapolation

Predicting outside the range of the training data.

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