AI_Resume_Analyzer_Presentation

1. AI Resume Analyzer using NLP &
Deep Learning
A Smart Solution for Resume
Screening & Analysis

2. Objective
• To develop an AI-powered Resume Analyzer
that helps recruiters and job seekers by
analyzing resumes, providing
recommendations, and ranking resumes based
on job descriptions.

3. Technologies Used
• - Frontend: HTML, CSS, JavaScript
• - Backend: Python (Flask/Django)
• - AI & NLP: Spacy, NLTK, TensorFlow, PyTorch
• - Database: PostgreSQL/MySQL
• - Deployment: AWS, Docker

4. Dataset Used (Kaggle)
• - Source: Kaggle
• - Name: Resume Dataset
• - Contains: Resumes, job descriptions, skills,
experience
• - Used for: Training AI models to analyze and
score resumes

5. Deep Learning Models Used
• - BERT for text processing
• - LSTM for sequential data analysis
• - CNN for feature extraction
• - TF-IDF for keyword extraction
• - Word2Vec for embedding resumes

6. Methodology
• 1. Data Collection from Kaggle
• 2. Preprocessing (Tokenization, Stopword
Removal)
• 3. Feature Extraction (TF-IDF, Word2Vec)
• 4. Model Training (LSTM, BERT)
• 5. Resume Ranking and Scoring
• 6. Deployment on Cloud

7. Features of the Application
• - HR can upload multiple resumes at once
• - AI ranks resumes based on job descriptions
• - Users get personalized resume feedback
• - Provides improvement suggestions
• - Secure and scalable cloud deployment

8. Future Enhancements
• - Integration with LinkedIn & Indeed
• - AI-based interview preparation
• - More datasets for training
• - Automated job matching
• - Multi-language resume analysis