This is Project which contains Data Visualization, EDA, Machine Learning Modelling for Checking the Sentiments.
Description Context Over 67k employee reviews for Google, Amazon, Facebook, Apple, and Microsoft
This dataset contains employee reviews separated into the following categories:
Index: index Company: Company name Location : This dataset is global, as such it may include the country's name in parenthesis [i.e "Toronto, ON(Canada)"]. However, if the location is in the USA then it will only include the city and state[i.e "Los Angeles, CA" ] Date Posted: in the following format MM DD, YYYY Job-Title: This string will also include whether the reviewer is a 'Current' or 'Former' Employee at the time of the review Summary: Short summary of employee review Pros: Pros Cons: Cons Overall Rating: 1-5 Work/Life Balance Rating: 1-5 Culture and Values Rating: 1-5 Career Opportunities Rating: 1-5 Comp & Benefits Rating: 1-5 Senior Management Rating: 1-5 Helpful Review Count: A count of how many people found the review to be helpful Link to Review : This will provide you with a direct link to the page that contains the review. However it is likely that this link will be outdated NOTE: 'none' is placed in all cells where no data value was found.
This data was scraped from Glassdoor
3 Inspiration To inspire people to create ML models to search for meaningful trends within this dataset