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Job Posting Classification

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Identify fake job postings!

Your friend is on the job market. However, they keep wasting time applying for fraudulent job postings. They have asked you to use your data skills to filter out fake postings and save them effort.

They have mentioned that job postings are abundant, so they would prefer that your solution risks filtering out real posts if it decreases the number of fraudulent posts they apply to.

You have access to a dataset consisting of approximately 18'000 job postings, containing both real and fake jobs.

The original source of the data can be found here, and the data dictionary can be found in the data_dictionary.ipynb file in your file browser!

import pandas as pd

df = pd.read_csv("fake_job_postings.csv")
df
df.info()
df.describe()
df.columns
df['fraudulent'].unique()
df[df['fraudulent'] == 1].count()
df['fraudulent'].value_counts()
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