Topic: tfidf-vectorizer Goto Github
Some thing interesting about tfidf-vectorizer
Some thing interesting about tfidf-vectorizer
tfidf-vectorizer,🖼️ Text2Meme is a Meme Classification Experiment based on Caption Text (Implemented as a Discord Bot)
User: abhishtagatya
tfidf-vectorizer,Recommendation system built using multiple ML models that aim to predict users' interests based on their past behavior and preferences.
User: adarshpalaskar1
Home Page: https://movie-recommender-6dk4.onrender.com/
tfidf-vectorizer,Feed Forward Neural Network for Twitter Sentiment Analysis Dataset
User: alexaapo
tfidf-vectorizer,Sentiment analysis of IMDB dataset.
User: ankit152
tfidf-vectorizer,A machine learning model that predicts tags for a given question and body.
User: ankit152
tfidf-vectorizer,Implementation of various Machine Learning and Deep Learning models for Sentiment Analysis on the 'Sentiment Labelled Sentences Data Set' by University of California, Irvine.
User: atharvajk98
tfidf-vectorizer,An NLP model to detect fake news and accurately classify a piece of news as REAL or FAKE trained on dataset provided by Kaggle.
User: chiraag-kakar
Home Page: https://chiraag-kakar.github.io/FUND
tfidf-vectorizer,Identify the Similar Questions asked on Quora Website by Using Hand_craft and Fuzzy String matching Algorithms
User: deepak2233
tfidf-vectorizer,Practicum Workshop
User: denis-mukhanov
Home Page: https://english-score.streamlit.app/
tfidf-vectorizer,Authorship Attribution with Machine Learning
User: faizann24
Home Page: https://faizanahmad.tech/blog/
tfidf-vectorizer,A comprehensive approach to implicit and explicit rating based recommendation engine
User: harshmudgil97
tfidf-vectorizer,
User: houssem96
tfidf-vectorizer,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.
User: iamjr15
tfidf-vectorizer,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%.
User: ksdkamesh99
tfidf-vectorizer,Scikit-learn tutorial for beginniers. How to perform classification, regression. How to measure machine learning model performacne acuuracy, presiccion, recall, ROC.
User: ksopyla
tfidf-vectorizer,Twitter Sentiment Analysis
User: mamutalib
tfidf-vectorizer,Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
User: mayurji
tfidf-vectorizer,This is final project of Information Retrieval course which is implementation of a search engine
User: mohammadtavakoli78
tfidf-vectorizer,📷🎥 Entity resolution system for SIGMOD 2020 programming contest
User: nikoletos-k
Home Page: https://nikoletos-k.github.io/Entity-resolution-SIGMOD-2020/
tfidf-vectorizer,NLP Classification - Bitcoin Tweet Sentiment
User: ntdoris
tfidf-vectorizer,TfidfVectorizer & PassiveAggressiveClassifier
User: ozlemekici
tfidf-vectorizer,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.
User: pemagrg1
tfidf-vectorizer,Performed text preprocessing, clustering and analyzed the data from different books using K-means, EM, Hierarchical clustering algorithms and calculated Kappa, Consistency, Cohesion or Silhouette for the same.
User: preetikumari18
tfidf-vectorizer,Movie recommender engine built on django
User: puskal-khadka
tfidf-vectorizer,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.
User: raj1603chdry
tfidf-vectorizer,All NLP related courses on DataCamp
User: rawan-kh
tfidf-vectorizer,Given a document, identifying the closest documents within the list of documents using tf-idf matrix and cosine similarity
User: rishabbh-sahu
tfidf-vectorizer,Detect Real or Fake News. To build a model to accurately classify a piece of news as REAL or FAKE. Using sklearn, build a TfidfVectorizer on the provided dataset. Then, initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares.
User: rishabh-karmakar
tfidf-vectorizer,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.
User: rjarman
Home Page: https://heaplinker.com
tfidf-vectorizer,A python package for creating content-based text recommender systems on pandas dataframes and SQLAlchemy tables
User: saheedniyi02
tfidf-vectorizer,Personalized anime recommendations based on collaborative filtering. Discover your next favorite anime!
User: sajid030
tfidf-vectorizer,This is a recommendation engine that recommends 10 courses related to course you search.
User: saket046
Home Page: https://coursera-course-recommender.herokuapp.com/
tfidf-vectorizer,Short Stories Recommendations.
User: sandeepurankar
tfidf-vectorizer,This repository contains introductory notebooks for text mining and web scrapping.
User: sanketmaneds
tfidf-vectorizer,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
User: sasivatsal7122
Home Page: https://cinematrix.subzeroo.tech/
tfidf-vectorizer,Weighted Class TFIDF technique to deal with imbalanced datasets
User: sauravpattnaikcs60
tfidf-vectorizer,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.
User: shaadclt
tfidf-vectorizer,E-Commerce Recommendation System
User: sherincheah
tfidf-vectorizer,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.
User: shubha23
tfidf-vectorizer,This repo contains code files of all the important topics of NLP.
User: sidharth178
tfidf-vectorizer,Using natural language processing to analyze the sentiments of people and detect suicidal ideation on online social content.
User: soumyajit4419
tfidf-vectorizer,For learning Purposes
User: tamanna18
tfidf-vectorizer,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
User: tejas-ta
Home Page: https://nlp-sms-spam-detection.wm.r.appspot.com
tfidf-vectorizer,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.
User: vaitybharati
tfidf-vectorizer,VIP Machine Learning Exercises and Practices
User: vipinjain1
tfidf-vectorizer,
User: vipinjain1
tfidf-vectorizer,Goal is to classify the given text under two categories:- Label 1 and Label 2.
User: vishal1999-33
tfidf-vectorizer,A text can be assigned more than one label
User: vishwa22
tfidf-vectorizer,Vietnamese Student Feedback Sentiment Analysis
User: vubacktracking
tfidf-vectorizer,Document Search Engine project with TF-IDF abd Google universal sentence encoder model
User: zayedrais
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