tfidf-vectorizer
There are 478 repositories under tfidf-vectorizer topic.
Mayurji/MLWithPytorch
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
zayedrais/DocumentSearchEngine
Document Search Engine project with TF-IDF abd Google universal sentence encoder model
soumyajit4419/AI_For_Social_Good
Using natural language processing to analyze the sentiments of people and detect suicidal ideation on online social content.
Sajid030/anime-recommendation-system
Personalized anime recommendations based on collaborative filtering. Discover your next favorite anime!
Losif01/text-preprocessing-to-transformers-NLP-notes
This repo is my personal notes from the Stanford NLP course, and i currently use it personally as a reference
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%.
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.
tamanna18/ML-NLP-DL
For learning Purposes
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.
SauravPattnaikCS60/Weighted-Class-Tfidf
Weighted Class TFIDF technique to deal with imbalanced datasets
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.
Ankit152/IMDB-sentiment-analysis
Sentiment analysis of IMDB dataset.
venkat-0706/Twalyze
Twitter sentiment analysis project using machine learning to classify tweets and understand audience mood, opinions, and behavior trends in real-time.
VipinJain1/VIP-Machine-Learning-Exercises-and-Practices
VIP Machine Learning Exercises and Practices
pemagrg1/Magic-Of-TFIDF
TFIDF being the most basic and simple topic in NLP, there's alot that can be done using TFIDF only! So, in this repo, I'll be adding the blog, TFIDF basics, wonders done using tfidf etc.
Tejas-TA/Transformer-BERT-SMS-Spam-Detection
Spam SMS Detection Project implemented using NLP & Transformers. DistilBERT - a hugging face Transformer model for text classification is used to fine-tune to best suit data to achieve the best results. Multinomial Naive Bayes achieved an F1 score of 0.94, the model was deployed on the Flask server. Application deployed in Google Cloud Platform
sasivatsal7122/Go_Screen-CineMatrix-ML-MODEL
This repo contains a machine learning model made using advanced and enhanced algos like KNN,SVD and also concepts like vectorization ,cosine similarity which predicts the similar movies for a given fav movie of user. So no more time wasting on searching for a good of you're choice
ozlemelo/detecting_fake_news
TfidfVectorizer & PassiveAggressiveClassifier
VuBacktracking/Deep-Neural-Network-Vietnamese-Student-Feedback-Sentiment-Analysis
Vietnamese Student Feedback Sentiment Analysis
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.
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.
faizann24/Authorship-Attribution
Authorship Attribution with Machine Learning
ksopyla/scikit-learn-tutorial
Scikit-learn tutorial for beginniers. How to perform classification, regression. How to measure machine learning model performacne acuuracy, presiccion, recall, ROC.
ryukaizen/marai
Conversational AI designed specifically for the Marathi language using Rasa.
Vishwa22/Multi-Label-Text-Classification
A text can be assigned more than one label
abhishtagatya/text2meme
🖼️ Text2Meme is a Meme Classification Experiment based on Caption Text (Implemented as a Discord Bot)
chiraag-kakar/FUND
An NLP model to detect fake news and accurately classify a piece of news as REAL or FAKE trained on dataset provided by Kaggle.
Nikoletos-K/Entity-resolution-SIGMOD-2020
📷🎥 Entity resolution system for SIGMOD 2020 programming contest
sherincheah/amz-ecom-recommender
E-Commerce Recommendation System
sidharth178/Natural-Language-Processing-Tutorial
This repo contains code files of all the important topics of NLP.
vaitybharati/Assignment-11-Text-Mining-01-Elon-Musk
Assignment-11-Text-Mining-01-Elon-Musk, Perform sentimental analysis on the Elon-musk tweets (Exlon-musk.csv), Text Preprocessing: remove both the leading and the trailing characters, removes empty strings, because they are considered in Python as False, Joining the list into one string/text, Remove Twitter username handles from a given twitter text. (Removes @usernames), Again Joining the list into one string/text, Remove Punctuation, Remove https or url within text, Converting into Text Tokens, Tokenization, Remove Stopwords, Normalize the data, Stemming (Optional), Lemmatization, Feature Extraction, Using BoW CountVectorizer, CountVectorizer with N-grams (Bigrams & Trigrams), TF-IDF Vectorizer, Generate Word Cloud, Named Entity Recognition (NER), Emotion Mining - Sentiment Analysis.
Denis-Mukhanov/english-score
Practicum Workshop
iambitttu/Sentiment-Analysis-Using-NLP
This project is to build sentiment analysis models capable of classifying text data into three categories: Positive, Negative, and Neutral sentiments.
iamjr15/Ensemble-AI-Text-Detection
This project detects AI-generated text using an ensemble of classifiers: Multinomial Naive Bayes, Logistic Regression, LightGBM, and CatBoost. It includes robust data preprocessing, model development, and evaluation, ensuring accurate identification of AI-generated content from a diverse text dataset.
kulwinderkk/recipe_recommender_nlp
This project is an unsupervised NLP-based recipe recommender system designed to provide personalized recipe suggestions. The system employs content-based filtering techniques, utilizing cosine similarity to measure the resemblance between user inputs and a database of recipes.
zenwor/equilibrium
🗞️ Article Management System