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Curso

Intermediate Predictive Analytics in Python

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Actualizado 04/2025

Learn how to prepare and organize your data for predictive analytics.

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PythonMachine Learning4 horas15 vídeos56 Exercícios4,350 XP5,787Certificado de conclusão

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Descrição do curso

Building good models only succeeds if you have a decent base table to start with. In this course you will learn how to construct a good base table, create variables and prepare your data for modeling. We finish with advanced topics on the matter.

Pré-requisitos

Introduction to Predictive Analytics in Python

1

Crucial base table concepts

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The basetable timeline

Timeline violations

Available data

Timeline violation

The population

Select the relevant population

A timeline compliant population

Removing duplicate objects

Calculate an event target

Calculate an aggregated target

2

Creating variables

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Adding fixed variables

Selecting the right value

Adding the donor segment

Adding living place

Adding aggregated variables

Selecting the appropriate date

Maximum value last year

Recency of donations

Adding evolutions

Ratio of last month's and last year's average

Absolute difference between two years

Using evolution variables

Performance of evolution variables

Meaning of evolution

3

Data preparation

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Creating dummies

Creating a dummy from a two-category variable

Creating dummies from a many-categories variable

Missing values

How to replace missing values

Creating a missing value dummy

Replace missing values with the median value

Replace missing values with a fixed value

Handling outliers

Influence of outliers on predictive models

Handle outliers with winsorization

Handle outliers with standard deviation

Transformations

Interactions

Square root transformation

Adding interactions to the basetable

4

Advanced base table concepts

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Seasonality

Seasonality or not

Detecting seasonality

The effect of seasonality

Using multiple snapshots

Target values

Calculating snapshot targets

Calculating aggregated variables

Stacking basetables

The timegap

Events during the timegap

Calculating aggregated variables with timegap

Adding age with timegap

Congratulations

Intermediate Predictive Analytics in Python

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