consumer-complaints

Multi-class text classifier that routes consumer complaints to the right product category using TF-IDF, LinearSVC and a CLI router.

Customer Complaint Intelligence Platform built on 15.95M CFPB complaints. Features executive analytics, company risk scoring, growth analysis, forecasting, recommendation engine, NLP classification, topic modeling, Streamlit dashboard, and Docker deployment.

End-to-end analysis of 2,000+ Comcast consumer complaints using EDA, time-series trends, state-wise visualization, NLP text preprocessing, and LDA topic modeling to uncover key insights on complaint patterns and resolution rates.

Deep Learning NLP project for consumer complaint classification using SimpleRNN, LSTM, GRU, and a fine-tuned DistilBERT Transformer with an interactive Gradio web application.

Analytics pipeline that turns CFPB consumer complaints into operational intelligence: topic discovery, interpretable risk scoring, and executive reporting.

Financial Consumer Complaints Data Analysis Using Tableau Dashboard - A Complete KPI Analysis Project

Interactive Power BI report on 1.4M CFPB consumer complaints (2023–2026): star schema, DAX measures, drill-through, and findings

End-to-end NLP project comparing TF-IDF + Logistic Regression and BERT for consumer complaint product classification using the CFPB complaint dataset.

Few-shot learning project classifying credit repair complaints by consumer knowledge level. Combines transformer embeddings, manual features, and multiple classifiers.

Telecom consumer complaints analysis — ticket trends, resolution rates and service quality insights using Python

Excel analysis of consumer complaints using geographic summaries, issue frequency analysis, date calculations and conditional formatting.

NLP on CFPB consumer-complaint narratives for 10 banks/fintechs: TF-IDF + NMF topics, template detection, quarterly alt-data signals in DuckDB vs. stock returns

Complaint routing, emerging-issue detection and similar-case search on 107k CFPB money-transfer and payment-app complaints: MinHash dedup, TF-IDF vs DistilBERT, topic burst detection, FAISS search, FastAPI.

Consumer Complaints Analysis Using BERT

Machine learning pipeline for classifying consumer complaint texts into product categories, with code, results, and screenshots. Built for Kaiburr Assessment 2025.

Analysis of 550K+ Consumer Financial Complaints using Python, Pandas and Power BI with dashboard insights and policy recommendations.

AI-powered NLP system for automatic consumer complaint classification and priority prediction using Machine Learning.

(Summer Internship I Project) This project involves the self-collected data processing and visualization of laptop specifications and consumer complaints. By synthesizing original datasets, the study identifies key reliability trends and hardware performance correlations through systematic visual analysis.

This Repository has files for a Google Cloud Platform Project for Coursework ADTA 5240 - Harvesting, Storing & Retrieving Data