Vicolas/Fake-Job-Posting-Prediction

Assessment For She Codes Africa. **Fake Job Posting Prediction** This Machine Learning project involves developing a model that can detect fraudulent job postings with the aim to help job seekers avoid falling prey to scams and to help companies identify and eliminate fraudulent job listings. The steps involves building a fake job posting prediction model with a dataset of job postings that have been labeled as both real and fake include: The dataset was made available by She Code Africa. Once the dataset was collected, it was cleaned and preprocessed, these involved removing irrelevant or redundant features and transforming the remaining features into a format suitable for machine learning algorithms. Next, a suitable machine learning algorithm was selected and trained on the preprocessed dataset. The chosen algorithm is a binary classifier that outputs either as 0 or a 1, indicating whether a job posting is real or fake. The performance of the model was evaluated using various metrics, such as accuracy, precision, recall, and F1 score.