You will get AI Resume Analyzer | Python, NLP, and GUI-based Resume Scoring Tool
Project details
The AI Resume Analyzer is a desktop application built with Python and advanced NLP models that intelligently analyzes and improves resume quality. Designed for job seekers, HR professionals, and resume consultants, it provides real-time feedback and actionable suggestions to elevate any resume.
The application processes PDF resumes to:
✅ Correct grammar using AI (via Hugging Face Transformers)
✅ Detect passive voice with spaCy
✅ Highlight weak or vague phrases
✅ Check for missing sections like Education, Work Experience, etc.
✅ Generate tailored improvement suggestions
✅ Provide a resume score out of 100 based on structure, clarity, and impact
The tool features a clean, user-friendly GUI using Tkinter, with multithreaded model loading for smooth performance. The resume is analyzed section-by-section, and results are displayed with color-coded panels and personalized tips.
The application processes PDF resumes to:
✅ Correct grammar using AI (via Hugging Face Transformers)
✅ Detect passive voice with spaCy
✅ Highlight weak or vague phrases
✅ Check for missing sections like Education, Work Experience, etc.
✅ Generate tailored improvement suggestions
✅ Provide a resume score out of 100 based on structure, clarity, and impact
The tool features a clean, user-friendly GUI using Tkinter, with multithreaded model loading for smooth performance. The resume is analyzed section-by-section, and results are displayed with color-coded panels and personalized tips.
Machine Learning Tools
PythonWhat's included
| Service Tiers |
Starter
$25
|
Standard
$50
|
Advanced
$75
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 15 days |
Number of Revisions | 0 | 0 | 0 |
Number of Model Variations | 1 | 2 | 2 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
About Muhammad
Artificial Intelligence, Machine Learning ,Data Analysis
Rawalpindi, Pakistan - 4:07 am local time
Passionate about solving real-world problems and actively pursuing opportunities to embrace new technologies.
Efficiency in python, computer Vision,data analysis and machine learning algorithms.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Gathering
Understand the client’s goals (personal use, HR automation, SaaS integration, etc.) Define target features (e.g., grammar correction, section analysis, scoring) Confirm input formats (PDF, DOCX, TXT) and output expectations
NLP Model Selection & Integration
Load and test the spaCy model for sentence parsing and passive voice detection Integrate HuggingFace Transformers for grammar correction (prithivida/grammar_error_correcter_v1) Use SentenceTransformers (all-MiniLM-L6-v2) for semantic section matching