tfidfvectorizer
There are 5 repositories under tfidfvectorizer topic.
ksdkamesh99 / Phony-News-Classifier
Phony News Classifier is a repository which contains analysis of a natural language processing application i.e fake news classifier with the help of various text preprocessing strategies like bag of words,tfidf vectorizer,lemmatization,Stemming with Naive bayes and other deep learning RNN (LSTM) and maintaining the detailed accuracy below
Language:Jupyter Notebook 11pemagrg1 / 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.
Language:Jupyter Notebook 8bumblebee26 / TheSocialComment-Challenge
Posts/Feeds recommendation engine based on content based and collaborative filtering methods
Language:Jupyter Notebook 7nano-bot01 / Movie-Recommender-Web-Application
Movie Recommendation System based on machine learning concepts
Language:Jupyter Notebook 7Bakar31 / Resume-Match-NLP
Hire the Perfect candidate. HackerEarth Competitions solution.
Language:Python 5chiraag-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.
Language:Jupyter Notebook 5RalphGradien / HomeWorkoutRecommendations
Python-based web application, Flask platform, utilizes a powerful Content-Based Filtering Algorithm to provide personalized recommendations excercises
Language:Python 4ramarav / Fake_News_Detection
Machine learning approach for fake news detection using Scikitlearn
Language:Jupyter Notebook 4AVINEET-Singh / Movie-Recommendation_System
In this project we are comparing two approaches for movie recommendation for a new user or existing user based on their age, gender, occupation.
Language:Python 3chandlergibbons / Machine-Learning-Medical-Transcription-Project
For our final project, our group chose to use a dataset (from Kaggle) that contained medical transcriptions and the respective medical specialties (4998 datapoints). We chose to implement multiple supervised classification machine learning models - after heavily working on the corpora - to see if we were able to correctly classify the medical specialty based on the transcription text.
Language:Jupyter Notebook 3kuldeep27396 / Real_News
Learned to detect fake news with Python. We took a political dataset, implemented a TfidfVectorizer, initialized a PassiveAggressiveClassifier, and fit our model. We ended up obtaining an accuracy of 92.82% in magnitude.
Language:Jupyter Notebook 3rochitasundar / Twitter-Sentiment-Analysis
Data consists of tweets scrapped using Twitter API. Objective is sentiment labelling using a lexicon approach, performing text pre-processing (such as language detection, tokenisation, normalisation, vectorisation), building pipelines for text classification models for sentiment analysis, followed by explainability of the final classifier
Language:Jupyter Notebook 3abdulkaaa / Deteksi-Berita-Palsu-dengan-Python
Penerapan TF-IDF Vectorizer dan Passive Aggressive Classifier dalam pendeteksian berita palsu dengan Python.
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LaurentVeyssier / Text-Classification-with-3-key-NLP-techniques
Use Key NLP techniques to classify news articles into categories: Bag_of_Words (tf-Idf), word embeddings and BERT language model
Language:Jupyter Notebook 2MingalievDinar / 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
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Fake News Prediction System using logistic regression, stopwords, nltk
Language:Jupyter Notebook 2Shubha23 / Fake-News-Detection-Text-Preprocessing-and-Classification
Fake new detection using text classification as real or fake news segments. Required installations - Python 3.8, NLTK, Scikit-Learn, Jupyter. Text cleaning, tokenization, vectorization, classification model generation and evaluation.
Language:Jupyter Notebook 2SonicStrain / News-Reliability-tester
Detecting 'FAKE' news using machine learning.
Language:Python 2Anshul21107 / SMS-Spam-Classifier
SMS Spam Classifier is a machine learning project that classifies SMS messages as either spam or not spam (ham).
Language:Jupyter Notebook 1curiousnish / fake-news-detector
Detect FAKE news using sklearn
Language:Jupyter Notebook 1harshith20 / emotion_detector
Machine learning model to predict emotions throught text
Language:Jupyter Notebook 1huangjunxin / Lite-sklearn-TfidfVectorizer
A Lite Implementation of sklearn TfidfVectorizer
Language:Jupyter Notebook 1ridhika123269 / Movie-Recommendation-System-using-ML
This projects aims to recommend movies to the user based on high similarity scores among them.
Language:Jupyter Notebook 1sanjjayrj / Chatbot-NLTK
A Simple conversational chatbot built using NLU concepts. The project uses reddit comments taken from 2015, which has about 1.7 billiion interactions.
Language:Python 1SannketNikam / Intents-based-Chatbot
Intents-Based Chatbot with Streamlit
Language:Jupyter Notebook 1Serfati / imdb_nlp
:robot: Sentiment Analysis using IMDb Reviews. The project contains TfidfVectorizer for representing text in numeric form. :movie_camera:
Language:Jupyter Notebook 1Thilagavijayan / Data_Dredge
This webapp helps to find the inaccurate information around the world through news
wolfsinem / product-tagging
Part of an internal project for my internship
Language:Jupyter Notebook 1aknafu12 / end-to-end-chatbot-python
This project is a Python-based data science end-to-end chatbot designed to autonomously handle conversations without the need for human intervention. Leveraging advanced natural language processing (NLP) techniques and machine learning algorithms, the chatbot is capable of understanding user queries, providing relevant responses.
Language:Jupyter Notebook 0elmezianech / Email-Spam-Ham-Classifier-LR
Email Classifier: A machine learning project using Python that categorizes emails into spam and ham (non-spam). Utilizes the Scikit-Learn library, employing logistic regression and TF-IDF (Term Frequency-Inverse Document Frequency) vectorization for text analysis and classification.
Language:Jupyter Notebook 0kirankonduru3 / Movie-reccomendation-system
A content-based recommender system that recommends movies similar to the movie plot and description
Language:Jupyter Notebook 0Russolves / Grade-Report-A.I.
Program that can take in large amounts of .csv files in the same directory and trains a deep learning neural network model based on the best/worst students evaluated by the user. Second program then utilizes the model from the first program to produce a projected report for each individual student inputted.
Language:Python 0wongkhoon / Professional-Data-Scientist-in-Python
Restrictions on sharing as advised by DataCamp
0mo-inkhan / TF-IDF-Vectorizer
Compute the TF-IDF matrix from a collection of documents to measure the importance of words for text analysis and information retrieval tasks.
Language:Python
