GitHub topics: tfidf-vectorizer
deoprakash/email-sms_spam_classifier
NLP based classifier classifying the email/SMS Spam or Not
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NamanKr24/Multi-Task-Ticket-Classifier
Traditional NLP pipeline for classifying support tickets by issue type & urgency while extracting key entities (products, dates, complaints). Built with sklearn, regex, TF-IDF, and deployed via Gradio.
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KaustavModak/Business-Aided-Customer-Feedback-Assessment-System
A Streamlit-based sentiment analysis app that classifies customer reviews into Positive, Neutral, or Negative using a pre-trained ML mode
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Ksschkw/MYRAGAGENT
My RAG Agent. . a fitting description.
Language: Python - Size: 67.4 KB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 0 - Forks: 0
SrijaAdhya12/project-to-interview
Your ultimate interview preparation kit for personal project related questions
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otuemre/EmailPhishingDetection
A real-time phishing email detection system using Machine Learning (SVM, Logistic Regression, Naive Bayes) with FastAPI backend and custom domain deployment.
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MuhammadUsman-Khan/Fake-News-Prediction
A machine learning model that predicts whether news is real or fake using Logistic Regression. Includes data cleaning with NLTK, TF-IDF feature extraction, and scikit-learn for modeling. Built in Google Colab to demonstrate text classification and misinformation detection.
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SridharYadav07/AI--Powered-Task-Management-System
An intelligent Task Management System that integrates Sentiment Analysis, Task Optimization, and Forecasting to streamline project and task handling. This AI-powered tool is designed to assist teams and project managers in making data-driven decisions by understanding emotional context, forecasting productivity, and optimizing workload distribution
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neon307-web/Discover-Your-Next-Favorite-Anime
Language: CSS - Size: 4.7 MB - Last synced at: 28 days ago - Pushed at: 28 days ago - Stars: 0 - Forks: 0
maximecharpentierdata/link-prediction
Link prediction in a citation network
Language: Python - Size: 10 MB - Last synced at: 26 days ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0
priyam-hub/Inside-Medium
Inside-Medium is an AI-powered content recommendation engine designed to help readers find the most relevant and high-quality Medium articles based on their interests or selected articles.
Language: Python - Size: 2.39 MB - Last synced at: 30 days ago - Pushed at: 30 days ago - Stars: 1 - Forks: 0
soumyajit4419/AI_For_Social_Good
Using natural language processing to analyze the sentiments of people and detect suicidal ideation on online social content.
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raj1603chdry/Fake-News-Detection-System
Fake News Detection System for detecting whether news is fake or not. The model is trained using "Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection. Link for dataset: https://arxiv.org/abs/1705.00648.
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RohanSardar/SpeechFlowGuard
A machine learning web API that detects toxic language in user comments using classical ML
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fatimesevilgen/email-spam-classifier
📩 Email spam classiffier with Multinomial NB & TFIDF Vectorizer and using Streamlit for Modern UI.
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Veer-Parikh/amazon-review-helpfulness
A machine learning project that predicts the helpfulness of Amazon customer reviews using NLP techniques, TF-IDF, and a Random Forest classifier.
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Shiva-Prasad-Naroju/News-Article-Classification-Using-NLP
🚀 Built a News Topic Classifier using NLP techniques with Logistic Regression and TF-IDF 💻✨ Developed and deployed an interactive, user-friendly Streamlit web app for real-time 📰 news classification and 📊 text analytics
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areebaghazal88/LLM-Generated-Text-Detection-Using-Machine-Learning
Machine learning pipeline to detect AI-generated text using logistic regression and TF-IDF features, including data preprocessing, training, and evaluation.
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venkat-0706/Twalyze
Twitter sentiment analysis project using machine learning to classify tweets and understand audience mood, opinions, and behavior trends in real-time.
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Jenson073/medical_chatbot
Medical assistent helper chatbot
Language: Python - Size: 464 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
Jenson073/Movie_review_sentiment_analysis
Positive or Negative review
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Shanmukhi1920/H-M-Recommendation-System
Develop personalized product recommendations for H&M's users using transaction history, customer data, and product metadata (including text descriptions) to enhance shopping experience and sustainability.
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ksdkamesh99/Spam-Classifier
A Natural Language Processing with SMS Data to predict whether the SMS is Spam/Ham with various ML Algorithms like multinomial-naive-bayes,logistic regression,svm,decision trees to compare accuracy and using various data cleaning and processing techniques like PorterStemmer,CountVectorizer,TFIDF Vetorizer,WordnetLemmatizer. It is implemented using LSTM and Word Embeddings to gain accuracy of 97.84%.
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psychomita/intelliCV
IntelliCV is an AI-driven platform for efficient and intelligent resume screening.
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Aliakbar-omidi/Sentiment-Review
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KKeshav1101/NLP
Based on Natural Language Programming Lab coursework as a part of my degree
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KeshavElangoDS/Mental-Health-Analysis-using-Social-Media-Data
Machine learning project to detect and classify mental health-related social media posts using NLP techniques for early intervention and awareness.
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singhkunwardeep/Twitter_sentiment_analysis
A machine learning project to classify Twitter sentiment into positive, negative, categories using Logistic Regression and TF-IDF Vectorization. This project involves data preprocessing, feature extraction, model training, and evaluation of the sentiment of tweets. Built with Python, NLTK, and Scikit-learn.
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sanjurajveer/Moview_review_analysis_NLP
Analysing movie reviews using NLP and categorising int good and bad
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lightxLK/SMBDuNLP
Making a project for detecting bots and fraud in social media using Deep Learning & NLP.
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RishabhYadav1202/Fake-News-Predictions
A machine learning project to classify news as real or fake using NLP techniques. Includes text preprocessing, TF-IDF, and models like Logistic Regression, Naive Bayes, and SVM, with SHAP for model explainability.
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JeffrinE/Inverted-Index-Search-Engine
A Document Search Engine with TF-IDF.
Language: Python - Size: 146 KB - Last synced at: 14 days ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0
ayomidee-e/twitter-sentiment-analysis
An NLP sentiment analysis model that classifies tweets into positive, negative, and neutral sentiments.
Language: Python - Size: 51.8 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0
Soumyapro/SMS-spam-classifier
A machine learning project that detects spam SMS messages using natural language processing techniques. The model analyzes text messages and accurately classifies them as spam or legitimate (ham).
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howard-haowen/NLP-demos
NLP demos and talks made with Jupyter Notebook and reveal.js
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TobiasPottier/LMR---Live-Movie-Recommendation
A full-stack project combining machine learning and web development to deliver smart movie recommendations. Built using Content-Based Filtering (CBF) with the MovieLens dataset and TMDB API, stored in MongoDB. Discover and get suggestions fast through a clean, responsive UI.
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akarshankapoor7/Automated-Complaint-Triage-System-using-NLP-and-Machine-Learning
Automated Severity Classification of Forum Complaints for Resolution Teams - Emphasizes automation and the end goal for resolution teams.
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INDDRSINGH/Movie-recommendation-system
After selecting a Movie from the list, ML model recommends 5 similar Movies.
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INDDRSINGH/Email-SMS-Spam-Classifier
Given a text, the ML model can predict whether it is "SPAM" or "NOT SPAM"
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khyatig0206/spam_detector
Introducing the Spam Detector Web App! This application is designed to detect spam comments using a K-Nearest Neighbors (KNN) classifier with TF-IDF vectorization. The web app is built using Django and HTMX, and it allows users to register, create comments, and detect spam within those comments.
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supriya811106/Twitter-Sentiment-Analysis
Analyzing the mood of tweets! We sort tweets on popular topics into positive, negative, or neutral categories to gauge public opinion. See what Twitter really thinks!
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thangtran3112/machine-learning
NLP, Neural networks, pytorch, tensorflow, AWS Sagemaker fine-tuning
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abhishtagatya/text2meme
🖼️ Text2Meme is a Meme Classification Experiment based on Caption Text (Implemented as a Discord Bot)
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abh2050/searchengine
This project is designed to facilitate advanced search functionality within legal documents using PySpark for data processing and Streamlit for the user interface. The system preprocesses the legal opinions, constructs an inverted index, calculates term frequencies, and other relevant metrics.
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TahirZia-1/NLP-TextClassify
A hands-on NLP project comparing classic ML models (Naïve Bayes, SVM, Logistic Regression) and ANNs for text classification using SMS Spam and 20 Newsgroups datasets.
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hperer02/Automated-essay-scoring
This repository contains my solution for the Kaggle competition Automated Essay Scoring 2.0. The goal of this project is to develop an automated system capable of scoring essays based on their content and quality using machine learning techniques.
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FaraazArsath/Customer-segmentation_E_commerce
Customer Segmentation of E commerce purchase database
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sambhu431/Medicine-Recommendation-System
The project aims to recommend medicines based on product uses similarity, side effects, and product review weightages. Powered by NLP techniques like TF-IDF and Cosine Similarity, the system provides intelligent and user-centric recommendations.
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chandkund/SMS-Spam-Detection
The goal is to develop a classification model that can accurately differentiate between spam and non-spam messages. This is crucial for applications like email filtering, SMS spam detection, and improving overall user experience by reducing the influx of unwanted or malicious content.
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Al-Hasib/NoCodeTextClassifier
A Python package for automatically training, evaluation, inference of Text Classification task with Low code/No Code
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hasanhammad/NLP-Final-Project
This repository contains code and dataset used in the final project of the NLP course in Iran University of Science and Technology
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aasthaj28/ai-for-social-good
Using natural language processing to analyze the sentiments of people and detect suicidal ideation on online social content.
Language: Jupyter Notebook - Size: 20 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0
junnwest/culinarypreproject
This project builds a machine learning model to predict a recipe’s cuisine based on its ingredients. Ingredients are cleaned, vectorized using TF-IDF, and reduced in dimensionality with PCA. Various models, including Logistic Regression, SVM, and Random Forest, are trained and evaluated to achieve accurate cuisine classification.
Language: Jupyter Notebook - Size: 15.2 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0
chandadiya2004/movie-recommendation-system
A Movie Recommendation System built using TfidfVectorizer and cosine similarity. The model processes a large dataset of movies and recommends similar movies based on a given input movie by analyzing textual features and calculating similarity scores.
Language: Python - Size: 95.3 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0
Abdelrahman-Amen/Active_Learning_in_NLP_using_Small_Text_Technique
This project demonstrates active learning for text classification using the Small-Text library on the IMDB dataset. A logistic regression model is trained iteratively, selecting the most uncertain samples for labeling with a smart query strategy. The approach highlights efficient learning with minimal labeled data, improving model performance.
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sumanthgubbala/Spam-Mail-Prediction-using-Machine-Learning
Language: Jupyter Notebook - Size: 12.7 KB - Last synced at: 5 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0
zayedrais/DocumentSearchEngine
Document Search Engine project with TF-IDF abd Google universal sentence encoder model
Language: Jupyter Notebook - Size: 28.6 MB - Last synced at: about 2 months ago - Pushed at: about 2 years ago - Stars: 53 - Forks: 24
radhe30/twitter-sentiment-analysis-NLP
This project analyzes the sentiment of tweets using natural language processing (NLP). It uses a dataset containing 1.6 million tweets, labeled as positive or negative, to train a machine learning model.
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Himank-Khatri/SpamHam
NLP models trained using Bag of Words (BoW), Term Frequency - Inverse Document Frequency (TF-IDF) and word2vec to classify SMS as Spam or Ham.
Language: Jupyter Notebook - Size: 345 KB - Last synced at: 4 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0
04bhavyaa/sms-spam-classification-system
A Machine Learning project that identifies whether a given message is spam or not. It uses Natural Language Processing (NLP) techniques (Stemming and TF-IDF Vectorization) for text transformation and a trained Multinomial Naive Bayes Classifier for predictions.
Language: Jupyter Notebook - Size: 1.89 MB - Last synced at: 11 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0
VishalPanchal11/NeuraLab-Nexus
NeuraLab Nexus (Full Stack MERN project for Tech enthusiasts) is an e-learning platform for Tech enthusiasts including courses, inbuilt collaborative coding environment having unique room id and a real time chatting space with file sharing.
Language: JavaScript - Size: 53.1 MB - Last synced at: 4 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0
leovidith/Toxic-Comment-Classification-TFIDF
Language: Jupyter Notebook - Size: 23.4 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0
VuBacktracking/Deep-Neural-Network-Vietnamese-Student-Feedback-Sentiment-Analysis
Vietnamese Student Feedback Sentiment Analysis
Language: Jupyter Notebook - Size: 34.4 MB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 7 - Forks: 0
zenwor/equilibrium
Article Management System, created as project for "Scripting Languages" course
Language: Jupyter Notebook - Size: 32.9 MB - Last synced at: about 1 month ago - Pushed at: 7 months ago - Stars: 2 - Forks: 0
jeffreywijaya100/youtube-comment-textmining
scrapping data komentar youtube yang berkaitan dengan machine learning dalam bahasa Indonesia sebanyak minimal 100 komentar
Language: Jupyter Notebook - Size: 2.54 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0
jeffreywijaya100/ecommerce-product-textmining
Pemodelan klasifikasi menggunakan data product dari sebuah ecommerce dengan ketentuan yang diberikan
Language: Jupyter Notebook - Size: 4.21 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0
anuragjain-git/text-classification
Train model using your own dataset and use it to predict the label for a given text. Additionally, it identify if the text is likely to be spam or irrelevant.
Language: Python - Size: 7.02 MB - Last synced at: 3 months ago - Pushed at: about 1 year ago - Stars: 3 - Forks: 0
Parag000/Content-Based-Movie-Recommender
This project builds a content-based movie recommendation system using the TMDB dataset. By combining metadata features like cast, genres, and directors into a "metadata soup," it calculates movie similarity with vectorizers (Count) and cosine similarity. Ideal for learning content-based filtering and text vectorization techniques.
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SKJNR/App-s-Review-Sentiment-Analysis
Perform Sentiment Analysis on App's Review Data
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lalan-desai/MRS-With-ML
A platform recommending movies based on user feedback and preferences using machine learning algorithm.
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radhe30/Spam-mail-prediction-Model
A machine learning model for spam mail prediction classifies incoming emails as either "spam" or "not spam" (ham) based on the content and other features.
Language: Jupyter Notebook - Size: 245 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0
mutalibcs/Twitter-Sentiment-Analysis
Twitter Sentiment Analysis
Language: Jupyter Notebook - Size: 37.2 MB - Last synced at: 6 months ago - Pushed at: 8 months ago - Stars: 3 - Forks: 0
rjarman/Bus-Mama
The Bus-Mama is a bus tracking mobile application for the transportation of the students of BSMRSTU. It helps the students of our university by showing the available route, bus, and their exact location. This app includes real-time bus tracking which is going to solve a problem that university students have been facing for many years. Students are often seen missing their buses. Often they can't maintain the bus time. Since there are many buses in our university, students can easily catch a bus if they know where and when it will pass by. My goal is to track the buses and make hardware, mobile application, and machine learning solution to solve the issue. This way the students can get relief from missing the bus and use the buses efficiently. The main idea is to track the buses. GPS trackers will be attached to every bus that will give the current position of them and automatically sync on the server. The Bus-Mama mobile application will show every real-time position of those buses. This application will be installed on students' mobile phones and in this way the students can easily maintain their transportation. In this application, the current location of the bus can be seen through Google map. Every bus will have a specific marker on Google map and all the details about a specific bus will be shown by clicking on the marker. There will be seen about how far the bus is, from which direction it will come, how much time to reach the bus, how much time it will take if there is any traffic on road, etc. There is also a search option to know about any specific bus details. There is also a list of all buses with sufficient details that will help students to know about all the details. Every student will have an account through which they can access bus data. Another main objective is the Bus-Mama Chatbot in the Bengali language so that the students can communicate to know about the bus easily. For now, they can make conversation only about bus-related information. The Chatbot is not yet able to make conversation except bus-related questions. If anyone asks anything except bus-related questions, it cannot reply to the question rather it will give a tag to the question as a reply. As the Chatbot is created in the Bengali language, it has used the "trie" data structure in lemmatization. A library has been designed to lemmatize the Bengali words. Almost 63,205 Bengali words have been lemmatized by using the library to train the SVM machine learning model.
Language: TypeScript - Size: 10 MB - Last synced at: 3 months ago - Pushed at: over 4 years ago - Stars: 14 - Forks: 1
sarrabenyahia/datamuse
Docker webapp on django - Parisian Culture - Datamuse
Language: HTML - Size: 13.9 MB - Last synced at: about 1 month ago - Pushed at: 8 months ago - Stars: 2 - Forks: 1
Ramneek2003/Movie-Recommendation-System
Developed as a warm-up project, this machine learning-based movie recommendation system utilizes cosine similarity to find and suggest similar films. By combining content-based filtering with popularity metrics, it provides personalized movie recommendations based on user preferences and trends, enhancing the overall user experience.
Language: Jupyter Notebook - Size: 5.1 MB - Last synced at: 4 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0
shaadclt/Password-Strength-Checker-RandomForestClassifier
This project is a password strength checker that utilizes a Random Forest Classifier to determine the strength of a given password. The Random Forest Classifier is trained on a dataset of passwords labeled with their corresponding strength levels.
Language: Jupyter Notebook - Size: 5.03 MB - Last synced at: 3 months ago - Pushed at: almost 2 years ago - Stars: 3 - Forks: 0
Team-Denis/HackYeah2024
Hackyeah2024 Cybersecurity Task
Language: Python - Size: 7.05 MB - Last synced at: 21 days ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
dynamicanupam/Classification_of_customer_complaints_using_NLP
Create a solution that will help in identifying the type of complaint ticket raised by the customers of a multinational bank using NLP and Topic Modelling (NMF)
Language: Jupyter Notebook - Size: 13.9 MB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
sanjanahombal/Study-on-Sentiment-Analysis
This project explores the optimal combination of Bag-of-Words and TF-IDF vectorization with Naive Bayes and SVM for sentiment analysis. It evaluates performance using accuracy, precision, recall, and F1-score, addressing ethical concerns like data privacy and bias to improve sentiment classification in real-world applications.
Language: Python - Size: 21.2 MB - Last synced at: 3 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
sanjanahombal/Sentiment-Analysis-using-Neural-Networks
This project explores sentiment analysis using neural networks
Language: Jupyter Notebook - Size: 7.03 MB - Last synced at: 3 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
chihiroanihr/COMP479-P4_F2022
Experiments with web crawling, scraping, and indexing a collection of web documents. Clustering the indexed data with k-means algorithm. Each resulting cluster is assigned a sentiment score using AFINN - a sentiment analysis script.
Language: Python - Size: 17.6 MB - Last synced at: 7 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
FYT3RP4TIL/TFIDF-EmotionDetection
Language: Jupyter Notebook - Size: 226 KB - Last synced at: 3 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0
pedrofracassi/insper-nlp-relevance-search
Busca por posts no Bluesky usando TFIDF para classificar relevância dos resultados
Language: Python - Size: 8.79 KB - Last synced at: 2 days ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0
Shubha23/Text-processing-NLP
This notebook contains entire text preprocessing pipeline for NLP problems. The ready-to-use functions require NLTK and SKlearn package installations. It also contains some prominent text classification models.
Language: Jupyter Notebook - Size: 529 KB - Last synced at: 4 months ago - Pushed at: over 4 years ago - Stars: 15 - Forks: 8
faseeh41/AI_For_Social_Good
Using natural language processing to analyze the sentiments of people and detect suicidal ideation on online social content.
Language: Jupyter Notebook - Size: 22 MB - Last synced at: 7 days ago - Pushed at: 11 months ago - Stars: 2 - Forks: 0
VaselaGousia/Fake-News-Detection-Using-Machine-Learning
Fake news on different platforms is spreading widely and is a matter of serious concern, as it causes social wars and permanent breakage of the bonds established among people. A lot of research is already going on focused on the classification of fake news. Here we will try to solve this issue with the help of machine learning in Python.
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engares/KNN-Based-Telegram-Chatbot-hosted-in-ESP32
A lightweight, customizable chatbot for Telegram running on an ESP32 microcontroller. It's optimized for low-resource environments and embedded systems projects.
Language: C++ - Size: 3.07 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 3 - Forks: 0
ryukaizen/marai
Conversational AI designed specifically for the Marathi language using Rasa.
Language: Python - Size: 35.2 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 5 - Forks: 0
Laoode/SentimentAnalysis_IMDB-Reviews
Sentiment Analysis of Film Review at IMDB using Linear Support Vector Classification
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ayusharma03/CodSoft_Internship
CodSoft Internship Projects containing, SMS Spam prediction Model, Customer Churn Prediction and Movie Classification System Based On the Movie's Summary
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bluntjudg/Book-Recommendation-System-
This project uses machine learning to create a personalized bookrecommendation system. By combining collaborative filtering and content-based filtering, it analyzes user preferences and book attributes to suggest tailored book recommendations. The system offers real-time updates and accurate predictions to enhance the user experience.
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Saket046/course-recommender
This is a recommendation engine that recommends 10 courses related to course you search.
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ardra-a-h/resume-parser
Language: Jupyter Notebook - Size: 155 KB - Last synced at: 3 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0
pthmhatre/StyleScribe-Using-Generative-Adversarial-Network
A fashion AI-based model capable of generating images from textual descriptions. The model should take natural language text as input and generate images that visually represent the given text. This text-to-image generation system bridges the gap between textual descriptions and visual content.
Size: 38.1 KB - Last synced at: 15 days ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0
TusharD48/SMS-Spam-Detection
This repository contains code and models for identifying spam SMS messages. It utilizes machine learning techniques to classify messages as spam or ham (non-spam).
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KirthanaShri/Medical-Text-Classification
Physician clinical notes categorized into medical specialities using ML model
Language: Python - Size: 13.7 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0
bhaskrr/restaurant-reviews-5-class-rating-prediction-
This repo contains the dataset and notebook for the kaggle restaurant reviews five class rating prediction
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SarveshwaranAM/email-spam-detection
This GitHub repository hosts a machine learning project for Email Spam Detection using Logistic Regression. Email spam, or unsolicited and irrelevant messages, is a prevalent issue that affects inboxes worldwide. This project provides a solution to identify and filter out spam emails with high accuracy.
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vinesh70/MailGuard-Intelligent-Spam-Detection
MailGuard is an intelligent spam detection tool that classifies emails as spam or ham using a Multinomial Naive Bayes model. Built with Streamlit, it leverages natural language processing techniques for text cleaning and feature extraction.
Language: Python - Size: 379 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0
mrtaz77/fitymi-Fake-It-Till-You-Make-It
Fake news detection using machine learning
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