Offered By: IBM
Classification Fundamentals for Marketing
This lab is dedicated to the study of machine learning classification methods. The goal is to determine the impact of marketing campaigns and predict whether customers will purchase the product.
Continue readingGuided Project
Artificial Intelligence
114 Enrolled4.6
At a Glance
This lab is dedicated to the study of machine learning classification methods. The goal is to determine the impact of marketing campaigns and predict whether customers will purchase the product.
The key problems to be solved in this lab involve classifying customers and analysing various marketing campaigns that are directed at them.
The crucial prerequisite for classification analysis is adequate data set preparation. Additionally, there are numerous alternative classification techniques that are currently available. Each of them has unique traits and analytical possibilities. This lab shows several classifiers in action and combines them into an ensemble. It also demonstrates ways to combine a pipeline during all phases of training preparation and analysis.
What you will learn
In this lab, we will learn how to download and pre-prepare data, classify and combine classifiers into an ensemble. This lab consists of the following steps:
- Download data - download and display data from a file
- Preliminary data preparation - preliminary analysis of data structure, change of data structure and tables
- Pipeline classification - classification and analysis by grouping stages
- Logistic regression - classification and analysis of accuracy and errors using logistic regression
- Over-sampling problem - solve the problem of uneven distribution of data
- Ensemble of classifiers - study various classifiers and methods of combining them into an ensemble
- Decision tree - shows how to visualize the decision tree and determine the importance of factors
Prerequisites
- Python - middle level
- Pandas - middle levelÂ
- Matplotlib - basic level
- SeaBorn - basic level
- Scikit-Learn - middle level