Analysing Amazon Product Reviews using Dimensions of Valence and Arousal in Python

Techniques:

OpenAI/GPT3, Random Forest Classification, SVM, Fast Clustering

Libraries Used:

1. Loading, exploring and manipulating datasets: pandas, numpy, random, google.colab
2. Error Handling for API calling and importing API keys from envirnoment: retry, time, os
3. Using gpt3 completions, embeddings and generating multiclass precion-recall: openai
4. For tokeizing text to perform validation for GPT3: transformers
5. ML models for classifiers, dimensionality reduction, model analysis: sklearn
6. For fast clustering and embeddings: sentence_transformers, torch
7. Visualisation: matplotlib
8. Model exports & imports: import pickle
9. for removing warnings: import warnings