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Author(s):

E.Sundara Vignesh | V.Sanjay | Mrs.A.Akileshwari
Keywords:

Career Recommendation, Machine Learning, Neural Networks, Job Scraping, Flask, Streamlit, AI Guidance System.
Abstract:
In The Modern World, Students And Professionals Often Face Difficulty Identifying Suitable Career Paths Aligned With Their Academic Performance, Technical Skills, And Personal Interests. This Paper Presents An AI-Based Career Path Recommendation System That Leverages Machine Learning And Deep Learning Models To Suggest Ideal Career Paths And Recommend Relevant Job Opportunities From Live Sources Such As Indeed And Naukri. The System Uses Random Forest And Neural Network Algorithms To Predict Suitable Career Categories From Academic And Skill Data, Achieving Meaningful Results In Multi-class Classification. It Integrates A Flask Backend, Streamlit Frontend, And SQLite Database, Forming A Robust, Data-driven Platform For Intelligent Career Guidance And Employment Matching.