ISR - Sentiment Analysis
Budget: $300 – $350 USD
The "airlines.csv" dataset contains airlines reviews over 360 airlines, the 'content' column has the users reviews, the rating(s) columns and the 'recommended' column referring to the review classification (Good : 1 / Bad : 0).
Rating columns consist of : 'overall_rating', 'seat_comfort_rating', 'cabin_staff_rating', 'food_beverages_rating', 'inflight_entertainment_rating', 'ground_service_rating', 'wifi_connectivity_rating', 'value_money_rating'.
The aim of the project is to create a sentiment analysis model which predicts the positivity from the negativity regarding airlines user reviews with efficiency.
Deliverables:
Code in the IPynb files which is runnable
Documentation with minimum of 6500 to 8000 words in word
An PPT with Presentation
Rating columns consist of : 'overall_rating', 'seat_comfort_rating', 'cabin_staff_rating', 'food_beverages_rating', 'inflight_entertainment_rating', 'ground_service_rating', 'wifi_connectivity_rating', 'value_money_rating'.
The aim of the project is to create a sentiment analysis model which predicts the positivity from the negativity regarding airlines user reviews with efficiency.
Deliverables:
Code in the IPynb files which is runnable
Documentation with minimum of 6500 to 8000 words in word
An PPT with Presentation