countvectorizer

tamanna18/ML-NLP-DL

For learning Purposes

AnupamMittal-21/Movie-Recommender-System

Unlock Your Next Favorite Film! Our NLP-powered Movie Recommendation Web App delivers tailored suggestions based on cast, genres, and production companies. Explore a seamless Streamlit interface, also, you can see the description of selected movie. and all movies list.

nikhilkr29/Email-Spam-Classifier-using-Naive-Bayes

A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of email subject is first used to train the classifier and then a previously unseen email subject is fed to predict whether it is Spam or Ham.

garg-priya-creator/Netflix-Recommendation-System

A web-app which can be used to get recommendations for a series/movie, the app recommends a list of media according to list of entered choices of movies/series in your preferred language using Python and Flask for backend and HTML, CSS and JavaScript for frontend.

Bakar31/Resume-Match-NLP

Hire the Perfect candidate. HackerEarth Competitions solution.

gabrielpreda/Support-Tickets-Classification

This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en

Bhavik-Ardeshna/Spam_SMS_Detection

Spam message detection using classifier

binnazcabuk/Sentiment-Analysis-in-Turkish-Film

Graduation Project/Sentiment Analysis in Turkish Film Reviews

Kawaljeet2001/Movie-Recommendation-System

This is the Movie Recommendation System project using a Content-Based recommender system trained on more than 5000 movies for generating movie recommendations based on user search.

mandar196/Hate_Speech_Detection-NLP

Created Hate speech detection model using Count Vectorizer & XGBoost Classifier with an Accuracy upto 0.9471, which can be used to predict tweets which are hate or non-hate.

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.

abhi7585/Movie-Recommendation-System

Using content-based approach to construct a suggestion for films. Films based on user feedback are recommended. By the machine learning model, all connected and equivalent films are suggested for the consumer.

avannaldas/EmailsClassification

Classification of emails received on a mass distribution group

charumakhijani/fake-and-real-news-detection

pleonova/jd-classifier

What is the difference between a data scientist and a data analyst? An NLP approach.

SudhanshuBlaze/Email-SMS-spam-detection

Used NLTK library from text pre-processing, Data Visualisation and Analysis done with matplotlib, used sklearn CountVectorizer and Tfidf transformer for feature extraction from text, then used Linear SVC algorithm to train the ML model. Got 99% accuracy.

Aman0807/NLP-in-Python-

Silicon Valley (TV Show on HBO) language analysis

buketgencaydin/Dynamic-Malware-Modelling

Malware classification using Extreme Gradient Boosting - XGBoost, CountVectorizer, TruncatedSVD

Chandrakant817/Semantic-Analysis-of-Restaurant-Reviews

Semantic Analysis of Restaurant Reviews (NLP Use Case)

chethanhn29/NLP_Projects

This is the Repository for different Natural language Processing(NLP) projects using Hugging face,Gensim, NLTK,Spacy and other Libraries

cltai9145/Multilabel-Text-Classification

Predicting Tags for Stack Overflow

ESMAaN/Amazon_Product_Reviews

Amazon Product Reviews: Sentiment Analysis with NLP

JUGG097/Kaggle-NLP-Competition-Real-or-Not

This competition is hosted by Kaggle https://www.kaggle.com/c/nlp-getting-started/overview. I participated in the competition in order to try my hands on the field of Artificial Intelligence known as Natural Language Processing.

lovpatel93/Kaggle-Spam

Spam Detection – Cluster SMS messages to “Spam” and “Ham” (Kaggle Challenge)

LunaticPrakash/Movie-Recommender

This project suggests you the list of movies based on the movie title that you have entered. It uses Count Vectorizer (Text-Feature Extraction tool) to find the relation between similar movies.

MingalievDinar/sentiment-analysis

The aim - is to develop a model that will give accurate predictions for the customer's test sample, but the training sample for is not given. It should be collected by parsing

NandakumarSG/sentiment--model-comparison

This project is to compare the F1 scores on performing sentiment analysis on reviews using various methods. We test the efficeintcy of TfidfVectorizer and CountVectrorizers when used with Multinomial Naive Bayes and SVC respectively.

rimmelasghar/Language-Detector-Model_Django

A Machine Learning Model that detects different language syntax.

samarth0174/SMS-SPAM-FILTERING

SMS SPAM FILTERING

ShubhamSharma476/Spam-Classifier-NLP

This is a machine learning project that focuses on detecting spam messages from regular messages. The project includes data cleaning and preprocessing, creating a bag of words model, and training the model using the Naive Bayes classifier. The final accuracy of the model is 98.39%.

ShubhamSharma476/Twitter_Sentiment_Analysis

I have done some Natural Language Processing on the Twitter US Airline Sentiment Dataset, which contains data for over 14000 tweets. Then I have used several classifiers namely, Support Vector Machine, Multinomial Naive Bayes, Random Forest and Decision Trees to predict the sentiment of the tweet i.e. positive, negative or neutral.

tonoy30/movie-recommender

A movie recommender system based on Content-Based Filtering using tmdb dataset

watcharap0n/m-business

linebot messengerbot @mango by fastapi

5hraddha/sentiment-analysis

An innovative system for filtering and categorizing movie reviews

anujchahal0001/LANGUAGE-DETECTION-MODEL-USING-Machine-Learning-AND-Natural-Language-Processing

"We used over 2000+ language rows to train our machine learning model, utilizing the scikit-learn library. Our model has achieved an accuracy of 95%."