This project is about sentiment analysis (text mining field), you can expect:

• data preparation (nulls and balance check, regex cleaning, label decoding, review length constraint, tokenization, vocabulary building)
• working with pretrained word embeddings (GloVe)
• data analysis (embedding coverage, detailed cleaning with regex, stop words, word clouds and count plots)
• modelling (CNNs, RNNs, VADER) with Cross Validation and error analysis (confusion matrix, misclassification examples analysis)
• experiments (review length and GloVe dimension sensitivity)
• 86% test set accuracy
• Jupyter Notebook report in English (a lot of Python code)

• Neural Networks
• NLP
• notebook
• Python