German wings review challenge

The notebook shows two use cases. The data is found in a text file holding a set of reviews about the German wings airline (airline code ‘4U’).

First use case:

The goal of this use case is to show that based on the customer review data how to predict the target variable 'Recommended'.

Second use case:

The goal of the second use case is to find topics in the reviews.

The notebook covers the following topics:

Data loading
- loading the customer review data from txt to dataframe
EDA
- plotting distribution of the variables
- plotting histograms
- showing relationship between target variables to other variables
- text analysis
  - plotting word frequencies
  - topic modeling with LDA
Feature engineering
- tfidf
- count features
- dimensionality reduction using truncated SVD
- word embedding
  - glove
Evaluation
- logloss
- roc curve
- precision recall curve
Machine learning models
- logistic regression
- navie bayes
- gradient boost machine
  - xgboost
- deep learning
  - lstm
  - gru
  - bidirectional lstm
Error analysis