Python-based web application, Flask platform, utilizes a powerful Content-Based Filtering Algorithm to provide personalized recommendations excercises

Hire the Perfect candidate. HackerEarth Competitions solution.

Penerapan TF-IDF Vectorizer dan Passive Aggressive Classifier dalam pendeteksian berita palsu dengan Python.

In this project we are comparing two approaches for movie recommendation for a new user or existing user based on their age, gender, occupation.

Detecting 'FAKE' news using machine learning.

Program that can take in large amounts of .csv files in the same directory and trains a deep learning neural network model based on the best/worst students evaluated by the user. Second program then utilizes the model from the first program to produce a projected report for each individual student inputted.

A Simple conversational chatbot built using NLU concepts. The project uses reddit comments taken from 2015, which has about 1.7 billiion interactions.

Creating a table/csv from multiple word form files

BERT model based sentiment analysis of tweets

A simple AI chatbot built using Python and Scikit-learn for basic intent recognition.

Machine learning model to detect and classify phishing emails using NLP and pattern analysis. Analyzes headers, sender behavior, and content to flag suspicious messages in real time.

ML Full text search system. Flask, Selenium parser, preprocessing, TF-IDF, Word2Vec

This project is about designing a Feedback Analysis by using various NLP Techniques which is commonly used in Recommendations System, and Chatbots.

Compute the TF-IDF matrix from a collection of documents to measure the importance of words for text analysis and information retrieval tasks.

HireSense is an AI-powered resume classifier that uses NLP and Machine Learning to predict the best-fit job role from a PDF resume. Built with Streamlit, it features a clean UI for uploading resumes and instantly suggests roles like Data Scientist, Full Stack Developer, and DevOps Engineer.