mUni Campuss 1 milestones 10 marks

Sentiment Analysis of Placement Data for Job Classification Using Naive Bayes and Suppo...

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

1
Milestones
0
Available mentors
0
Enrolled students
2
Core skills
About this project

Sentiment Analysis of Placement Data for Job Classification Using Naive Bayes and Support Vector Machine

Milestones
1. Project Idea Approval
10 marks 5d
test
Open internships using this project -->
Skills you'll learn
Natural Language Processing (NLP) Machine Learning (Naive BayesSVM) Python Programming Data Cleaning & Tokenization Text Classification
Tools used
Python (NLTKscikit-learnpandasmatplotlib) Jupyter Notebooks Google Colab (for execution) CSV or survey datasets
Prerequisites
Basics of NLP Understanding of supervised learning Python basics and libraries (scikit-learnpandas)
Available mentors

No mentors have signed up for this project yet.

Be the first to mentor
Share
You'll earn — Certificate (PDF)

AICTE-aligned Project Completion Certificate

A formal, audit-ready PDF certificate issued by Assessfy + your institute on successful completion. Includes AICTE credit hours, your evaluator's signature, and a QR code for third-party verification.

Certificate of Project Completion

This is to certify that

has successfully completed the project

Sentiment Analysis of Placement Data for Job Classification…

Auto-issued on completion QR-verifiable
You'll earn — Digital Badge

Shareable LinkedIn / Resume Skill Badge

A compact, verifiable Open-Badges-2.0-compliant digital credential. Add to your LinkedIn profile, GitHub README, or resume in one click. Recruiters can validate authenticity via a unique URL.

Sentiment Analysis of Placement Data …
Assessfy
Auto-issued on completion One-click LinkedIn add

Similar Projects you might like

Hand-picked by the recommender from your program & skill area.

Relevant Certifications to boost your application

From the Assessfy Certification library — take one and add it to your resume / LinkedIn before applying.

10 marks
Sign up & enroll