countvectorizer

There are 0 repository under countvectorizer topic.

grocery_recommendation
melodygr / grocery_recommendation
Grocery Recommendation on Instacart Data
market-basket-analysis surprise-python nlp-machine-learning countvectorizer cosine-similarity clustering kmeans-clustering collaborative-filtering content-based-recommendation flask
Language:Jupyter Notebook 26
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.
cosine-similarity countvectorizer machine-learning natural-language-processing recommender-system
Language:Python 21
tamanna18 / ML-NLP-DL
For learning Purposes
ml nlp-machine-learning deep-learning machine-learning reinforcement-learning information-retrieval data-mining bag-of-words natural-language-processing nlp classification classification-algorithm countvectorizer tfidf-vectorizer tokenizer
Language:Jupyter Notebook 15
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.
cosine-similarity-scores countvectorizer css flask html html-css-javascript netfl python recommendation-system netflix-recommendation-system
Language:Jupyter Notebook 12
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.
naive-bayes-classifier spam-classification spam-detection countvectorizer machinelearning
Language:Jupyter Notebook 12
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
natural-language-processing predictive-modeling classification-model naive-bayes-classifier support-vector-machines lightgbm countvectorizer tfidf-text-analysis python pandas scikit-learn flask numpy
Language:Python 8
abubakarsiddik31 / Resume-Match-NLP
Hire the Perfect candidate. HackerEarth Competitions solution.
machine-learning nlp-machine-learning resume tfidfvectorizer countvectorizer
Language:Python 6
Bhavik-Ardeshna / Spam_SMS_Detection
Spam message detection using classifier
svm-classifier naive-bayes-classifier machine-learning sklearn countvectorizer natural-language-processing nltk
Language:Jupyter Notebook 5
binnazcabuk / Sentiment-Analysis-in-Turkish-Film
Graduation Project/Sentiment Analysis in Turkish Film Reviews
python nlp-machine-learning machine-learning navie-bayes-algorithm tf-idf countvectorizer zemberek svm logistic-regression seaborn nltk-library
Language:Python 5
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.
python nlp porter-stemmer hatespeech countvectorizer text-classification xgboost-classifier
Language:Jupyter Notebook 5
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.
text-mining tweets-dataset sentiment-analysis correlation-analysis sentiment-value sentiment-score affinity-scores emotion-lexicon emotion-mining named-entity-recognition pos-tagging word-cloud tfidf-vectorizer n-grams countvectorizer feature-extraction text-preprocessing tokenization clean-tweets lemmatization
Language:Jupyter Notebook 5
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.
cosine-similarity countvectorizer movie-recommendation
Language:Jupyter Notebook 4
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.
reactjs react-router flask tmdb-api scikit-learn pandas heroku axios movie-recommendation css js countvectorizer
Language:Jupyter Notebook 4
avannaldas / EmailsClassification
Classification of emails received on a mass distribution group
countvectorizer email-classifier scikit-learn sklearn text-classification tfidf
Language:Jupyter Notebook 3
charumakhijani / fake-and-real-news-detection
news-dataset kaggle-dataset fake-real-news-dataset nlp stemming lemmatization word-embeddings countvectorizer tf-idf-vectorizer onehot-encoding onehot-encoder sequence-padding glove-embeddings lstm gru gru-model lstm-model neural-networks reducelearningrate early-stopping
Language:Jupyter Notebook 3
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.
movie-recommendation imdb movies python countvectorizer nlp natural-language-processing movies-reviews
Language:JavaScript 3
pleonova / jd-classifier
What is the difference between a data scientist and a data analyst? An NLP approach.
nlp naive-bayes-classifier countvectorizer tornado-chart
Language:Python 3
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.
natural-language-processing naive-bayes-classifier sklearn nltk countvectorizer tfidf text-classification text-processing
Language:Jupyter Notebook 3
Aman0807 / NLP-in-Python-
Silicon Valley (TV Show on HBO) language analysis
nlp sentiment-analysis wordcloud countvectorizer tweepy natural-language-processing python pandas scikit-learn beautifulsoup datacollection dataanalysisandmlusingpython
Language:Jupyter Notebook 2
buketgencaydin / Dynamic-Malware-Modelling
Malware classification using Extreme Gradient Boosting - XGBoost, CountVectorizer, TruncatedSVD
countvectorizer cross-validation hyperparameter-tuning machine-learning python truncated-svd xgboost
Language:Jupyter Notebook 2
Chandrakant817 / Semantic-Analysis-of-Restaurant-Reviews
Semantic Analysis of Restaurant Reviews (NLP Use Case)
countvectorizer machine-learning naive-bayes naive-bayes-classifier nlp reviews sentiment-analysis
Language:C 2
chethanhn29 / NLP_Projects
This is the Repository for different Natural language Processing(NLP) projects using Hugging face,Gensim, NLTK,Spacy and other Libraries
anomaly-detection attention-is-all-you-need bag-of-words bilstm countvectorizer lemmatization lstm-neural-networks ngrams onehot-encoding rnn stemming text-classification text-to-speech transfer-learning transformers word2vec
Language:Jupyter Notebook 2
cltai9145 / Multilabel-Text-Classification
Predicting Tags for Stack Overflow
tfidf-vectorizer countvectorizer decisiontreeclassifier
Language:HTML 2
ESMAaN / Amazon_Product_Reviews
Amazon Product Reviews: Sentiment Analysis with NLP
countvectorizer machine-learning-algorithms nlp-machine-learning nltk-tokenizer python-3 xgboost-classifier kaggle
Language:Jupyter Notebook 2
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.
nlp-machine-learning pipeline feature-extraction kaggle-competition natural-language-processing tfidf-vectorizer countvectorizer feature-engineering transformer
Language:Jupyter Notebook 2
lovpatel93 / Kaggle-Spam
Spam Detection – Cluster SMS messages to “Spam” and “Ham” (Kaggle Challenge)
nlp-machine-learning nlp-keywords-extraction natural-language-processing nltk-python nltklib tokenization stemming vectorization bag-of-words countvectorizer feature-engineering ensemble-classifier ensemble-machine-learning random-forest-classifier gridsearchcv lemmatization tf-idf tf-idf-vectorizer cross-validation evaluation-metrics
Language:Jupyter Notebook 2
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
sentiment-analysis parsing countvectorizer tfidfvectorizer nlp bs4 scrapper beautifulsoup scraping-websites
Language:Jupyter Notebook 2
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.
sentiment-analysis python jupyter-notebook colab-notebook naive-bayes-classifier svm-classifier countvectorizer tfidf
Language:Jupyter Notebook 2
rahulg-101 / Youtube-Comment-Spam-Detection
This project aims to develop a machine learning algorithm that can accurately detect and filter out spam comments on YouTube videos.
algorithms bernoulli-naive-bayes machine-learning python supervised-learning tfidf-vectorizer countvectorizer numpy pandas
Language:Python 2
RahulRmCoder / CraveCrafters-Food-App
CraveCrafters is an AI-powered food ordering web application that seamlessly integrates a chatbot to assist users with menu browsing, order placement, and customer service. The system features a Node.js backend, a FastAPI-based chatbot, and an interactive frontend built with HTML, CSS, and JavaScript. It utilizes MongoDB as its database.
express-js chatbot cosine-similarity countvectorizer css express-middleware fastapi generative-ai groq-api html javascript mongodb node-js recommender-system rest-api sklearn smtlib
Language:HTML 2
rimmelasghar / Language-Detector-Model_Django
A Machine Learning Model that detects different language syntax.
countvectorizer django machine-learning ml python3
Language:Python 2
samarth0174 / SMS-SPAM-FILTERING
SMS SPAM FILTERING
spam-filtering countvectorizer machine-learning-algorithms nlp
Language:Jupyter Notebook 2
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%.
countvectorizer machine-learning natural-language-processing nltk numpy pandas
Language:Jupyter Notebook 2
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.
countvectorizer machine-learning natural-language-processing nltk numpy pandas sentiment-analysis tf-idf
Language:Jupyter Notebook 2
tonoy30 / movie-recommender
A movie recommender system based on Content-Based Filtering using tmdb dataset
cosine-distance cosine-similarity countvectorizer fastapi numpy pandas nltk sklearn
Language:Jupyter Notebook 2
watcharap0n / m-business
linebot messengerbot @mango by fastapi
rest-api heroku fastapi-template line-bot-sdk chatbot tokenizer pytorch countvectorizer multinomial-naive-bayes
Language:Jupyter Notebook 2

countvectorizer

melodygr / grocery_recommendation

AnupamMittal-21 / Movie-Recommender-System

tamanna18 / ML-NLP-DL

garg-priya-creator / Netflix-Recommendation-System

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

gabrielpreda / Support-Tickets-Classification

abubakarsiddik31 / Resume-Match-NLP

Bhavik-Ardeshna / Spam_SMS_Detection

binnazcabuk / Sentiment-Analysis-in-Turkish-Film

mandar196 / Hate_Speech_Detection-NLP

vaitybharati / Assignment-11-Text-Mining-01-Elon-Musk

abhi7585 / Movie-Recommendation-System

Kawaljeet2001 / Movie-Recommendation-System

avannaldas / EmailsClassification

charumakhijani / fake-and-real-news-detection

LunaticPrakash / Movie-Recommender

pleonova / jd-classifier

SudhanshuBlaze / Email-SMS-spam-detection

Aman0807 / NLP-in-Python-

buketgencaydin / Dynamic-Malware-Modelling

Chandrakant817 / Semantic-Analysis-of-Restaurant-Reviews

chethanhn29 / NLP_Projects

cltai9145 / Multilabel-Text-Classification

ESMAaN / Amazon_Product_Reviews

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

lovpatel93 / Kaggle-Spam

MingalievDinar / sentiment-analysis

NandakumarSG / sentiment--model-comparison

rahulg-101 / Youtube-Comment-Spam-Detection

RahulRmCoder / CraveCrafters-Food-App

rimmelasghar / Language-Detector-Model_Django

samarth0174 / SMS-SPAM-FILTERING

ShubhamSharma476 / Spam-Classifier-NLP

ShubhamSharma476 / Twitter_Sentiment_Analysis

tonoy30 / movie-recommender

watcharap0n / m-business