At a Glance

Name: The task of spam classification in cybersecurity
Price: Free CAD
Rating: 5.0 (8 reviews)
Author: bogdan_norkin, sergii_kavun_2

The aim of this laboratory work is to create models of machine and deep learning at the intersection of the fields of NLP and Network Security using the SMS Spam Collection dataset with the help of frameworks and libraries.

Objective of the Laboratory Work

Creating machine learning and deep learning models at the intersection of NLP and Network Security using the SMS Spam Collection dataset with auxiliary frameworks and libraries.

To complete this laboratory, you need to:

Quickly familiarize yourself with the SMS Spam Collection dataset and build the best models using functional programming and layered model description to solve the spam classification problem.
Show various performance metrics of the built models.
Change the values of some hyperparameters to improve the model training process and achieve the best results.
Visualize the results of data analysis using different types of charts.

What You Will Need

To complete the course, you need to have knowledge of the following libraries:

pandas
matplotlib
numpy
tensorflow
keras

This platform works best with the latest versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.

Instructions

Follow the instructions outlined in the laboratory work
Replace ##YOUR CODE GOES HERE## with your python code.

Offered By: IBM

The task of spam classification in cybersecurity

At a Glance

Objective of the Laboratory Work

To complete this laboratory, you need to:

What You Will Need

Instructions