Fall-Rise

High Rise

Low Rise

Low Fall

Low Rise

Level Tone

(y - y`)2 / 2N

(y - y`) / N

(y - y`) / 2N

(y - y`)

Model evaluation

Model deployment

Data cleaning

Feature engineering

Replace missing values with the mean of the column.

Impute missing values using linear regression

Replace missing values with the mode (most frequent value) of the column

Replace missing values with random noise

Data visualization

Data aggregation

Data normalization

Data storage

Pie charts fail to represent proportions when categories are not mutually exclusive.

 Pie charts are less visually appealing than bar charts.

 Pie charts provide limited precision when comparing the sizes of slices.

Pie charts are not as effective as line charts for representing trends over time.

The L1 norm adds a penalty proportional to the absolute values of the coefficients, leading to sparse solutions

The L1 norm encourages all coefficients to be close to zero but not exactly zero.

The L1 norm is less effective than the L2 norm for high-dimensional data.

The L1 norm is the sum of the squared values of the coefficients

Use a 3D bar chart to show more complex patterns

 Increase the number of bars to include every category on the chart.

Group categories into broader categories to reduce the number of bars.

Use a pie chart instead of a bar chart.

Intervals

Range

Quantiles

Whiskers