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Once you have finished solving the exercises, be sure to commit your changes, push to your repository and go to 4Geeks.com to upload the repository link.
We want to implement a system that is able to automatically detect whether a web page contains spam or not based on its URL.
The dataset can be found in this project folder under the name url_spam.csv
. You can load it into the code directly from the link (https://raw.githubusercontent.com/4GeeksAcademy/NLP-project-tutorial/main/url_spam.csv
) or download it and add it by hand in your repository.
Use what we have seen in this module to transform the data to make it compatible with the model we want to train. Segment the URLs into parts according to their punctuation marks, remove stopwords, lemmatize, and so on.
Make sure to conveniently split the dataset into train
and test
as we have seen in previous lessons.
Start solving the problem by implementing an SVM with the default parameters. Train it and analyze its results.
After training the SVM, optimize its hyperparameters using a grid search or a random search.
Store the model in the corresponding folder.
NOTE: Solution: https://github.com/4GeeksAcademy/NLP-project-tutorial/blob/main/solution.ipynb
Signup and get access to similar projects
Every week, we pick a real-life project to build your portfolio and get ready for a job. All projects are built with ChatGPT as co-pilot!
Start the ChallengeA tech-culture podcast where you learn to fight the enemies that blocks your way to become a successful professional in tech.
Listen the podcast