Scrape job websites into a single spreadsheet with no duplicates.

The high-performance .NET search engine based on pattern recognition.

This repository is for my students of Udemy. You can find all lecture codes along with mentioned files for reading in here. So, feel free to clone it and if you have any problem just raise a question.

Information Retrieval algorithms developed in python. To follow the blog posts, click on the link:

Analisis Sentimen Twitter dengan TFIDF-ANN

BERT, LDA, and TFIDF based keyword extraction in Python

Fast Full Text Search based on BM25

[SOICT 2024] LLM-Powered Video Search: A Comprehensive Multimedia Retrieval System

A simple tool to generate tags for the given text (document) using TF-IDF.

Machine Learning for Phishing Website Detection

Document Search Engine project with TF-IDF abd Google universal sentence encoder model

This is retrieval based Chatbot based on FAQs found at a banking website.

A complete NLP and Machine Learning project to detect fake and real news using TF-IDF and Logistic Regression. Includes full training pipeline, evaluation charts, and an interactive Streamlit web app for real-time credibility analysis. Dataset adapted from Kaggle’s Fake and Real News Dataset.

Detect plagiarism of Github repositories in someone else's code

NLP tutorial

Here I sort out some small projects I did in the process of learning NLP.

Text clustering with K-means and tf-idf

A web app that classifies text as a spam or ham. I am using my own ML algorithm in the backend, Code to that can be found under machine_learning_section. For Live Demo: Checkout this link

Using Spacy and NLTK module with Tf-Idf algorithm for text-summarisation. This code will give you the summary of inputted article. You can input text directly or from .txt file, .pdf file or from wikipedia url.

The project is based on a multi-label classification problem in NLP.

A content-based recommender system for books using the Project Gutenberg text corpus

Cereja is a bundle of useful functions we don't want to rewrite and .. just pure fun!

Developed BERT, LSTM, TFIDF, and Word2Vec models to analyze social media data, extracting service aspects and sentiments from a custom dataset. Provided actionable insights to telecom operators for customer satisfaction and competitive analysis.

計算關鍵詞重要程度(TF-IDF實作)Calculate cosine-similarity between documents using TF-IDF

A detailed educational guide explaining two essential NLP techniques, TF-IDF and Word2Vec. Learn how text is transformed into numerical vectors, compare their mathematical foundations, explore real-world use cases, and implement both methods in Python for text analysis and machine learning.

An AI-powered Fake Review Detector built with Python, Streamlit, and Scikit-learn. Uses TF-IDF vectorization, Logistic Regression, and behavioral text analytics (sentiment, exclamations, clichés) to identify synthetic or spammy product reviews. Includes training scripts and a full interactive dashboard.

Two-part information retrieval system: 1) Pre-process text files, generate TF-IDF matrix and inverted index. 2) Retrieve relevant documents ranked by cosine similarity for given queries.

Finding recommendations between all MangaDex manga

Product Categorization with Machine Learning

利用sklearn和gensim中的tfidf,lsa,doc2vec进行查询与文档匹配搜索