Skip to content

ML Text Classification project, training a model to differenciate Spam and Ham SMS messages

Notifications You must be signed in to change notification settings

cc231025/Ham-Detection

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

12 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Training ML Models to Classify text messages as SPAM or HAM

Group Ham: Alikhan Manat, Aleksandar Miloradovic & Jakob Huber

In this Project we set out to train different ML Models to classify Text from the SMS Spam Dataset. We trained 3 different Models trying to get an accuracy as good as possible and also including some Tools to Explain the Models.

To Run this Notebook with the provided Environment

  • You need to have Anaconda or Miniconda installed
  • Use Anaconda Prompt to execute the following commands
  • create the Environment conda env create -f environment.yml
  • Activate the Environment: conda activate hamEnv
  • start your Jupiter Notebook: jupyter lab

If you want the kernel to show up in your Jupiter Interface you might need to additionally run: python -m ipykernel install --user --name=hamEnv --display-name "Python (hamEnv)"

If ipykernel is not installed additionally run pip install ipykernel

With this setup if you open your jupiter notebok you can simply select the hamEnv as your kernel. This gives you a fixed and working environment including all necessary dependencies without any additional installs!

About

ML Text Classification project, training a model to differenciate Spam and Ham SMS messages

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 100.0%