British Airways Customer Reviews Analysis
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Data Scientist
Data Scraper
Data Visualizer
Python
Selenium
TensorFlow
Task 1: Web Scraping for Company Insights
Objective: Extract and analyze airline reviews from Skytrax to gain valuable insights.
Steps:
Data Collection: Scrape review data from Skytrax using Python and Jupyter Notebook.
Data Cleaning: Prepare the messy text data for analysis by cleaning and preprocessing it.
Data Analysis: Employ techniques like topic modeling, sentiment analysis, or wordclouds to uncover insights from the reviews.
Presentation: Summarize findings in a single PowerPoint slide, including visualizations, metrics, and concise explanations.
Task 2: Predicting Customer Buying Behavior
Objective: Build a machine learning model to predict customer bookings based on given dataset.
Steps:
Data Exploration: Analyze the dataset to understand its structure and statistics.
Data Preparation: Prepare the data for modeling, including feature engineering if necessary.
Model Training: Train a RandomForest model to predict customer bookings.
Model Evaluation: Evaluate model performance using cross-validation and metrics.
Variable Importance: Analyze variable contributions to the model's predictive power.
Presentation: Summarize findings in a single PowerPoint slide, including visualizations and key insights.
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Posted Sep 4, 2024
Scraped customer reviews from Skytrax, Cleaned data, did Sentiment Analysis, Visualized it, predicted if the customer were to complete booking or not on dataset
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Tags
Data Scientist
Data Scraper
Data Visualizer
Python
Selenium
TensorFlow
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