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NLP for Customer Support Automation

This project applies Natural Language Processing (NLP) and Machine Learning techniques to categorize customer support tickets and enhance response automation. The main goal is to improve support efficiency, reduce resolution time, and boost customer satisfaction.


Project Overview

Customer support teams receive thousands of tickets daily. Manual triage leads to delays and inefficiencies. This project leverages text classification using NLP and ML models to:

  • Automatically classify support tickets into categories.
  • Understand common issues using ticket descriptions.
  • Help build an automated response system.

Objectives

  • Develop an NLP model for automated ticket classification.
  • Categorize customer inquiries into meaningful topics.
  • Achieve classification accuracy of at least 85%.
  • Reduce response time for frequent issues by 20%.

Tech Stack

  • Python (Pandas, NumPy)
  • Scikit-learn
  • TfidfVectorizer
  • Random Forest, Logistic Regression, SVM, Naive Bayes
  • Jupyter Notebook

Author

Jagadeeswari Suvvari
Student @ RGUKT Srikakulam
Aspiring to automate the future with ML & NLP 🚀

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NLP machine-learning customer-support text-classification tfidf scikit-learn automation

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