Topic: countvectorizer Goto Github
Some thing interesting about countvectorizer
Some thing interesting about countvectorizer
countvectorizer,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.
User: abhi7585
countvectorizer,Silicon Valley (TV Show on HBO) language analysis
User: aman0807
countvectorizer,Basic NLP Hands-on. Data Cleaning, Pre-processing, Tokenization, Vectorization (Tf-Idf, Count vectorizer, Presence/Absence vectorization etc.) using NLTK and sklearn library.
User: anikch
countvectorizer,Sentiment Analysis on Airline Industries Customer Feedback Data
User: ankush105
Home Page: https://www.flysafe-analytics.com
countvectorizer,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.
User: anupammittal-21
Home Page: https://movie-recommender-syst.streamlit.app/
countvectorizer,Classification of emails received on a mass distribution group
User: avannaldas
countvectorizer,Hire the Perfect candidate. HackerEarth Competitions solution.
User: bakar31
countvectorizer,Movie Recommendation System powered by Python machine learning algorithms and the Streamlit framework. Get personalized movie suggestions based on your viewing history and preferences, all at the click of a button. Streamline your movie selection process today and enjoy a stress-free movie night every time.
User: bathinamahesh
countvectorizer,Spam message detection using classifier
User: bhavik-ardeshna
Home Page: https://www.kaggle.com/bhavikardeshna/spam-message-detection-using-svm-and-naive-bayes
countvectorizer,Graduation Project/Sentiment Analysis in Turkish Film Reviews
User: binnazcabuk
countvectorizer,Malware classification using Extreme Gradient Boosting - XGBoost, CountVectorizer, TruncatedSVD
User: buketgencaydin
countvectorizer,Semantic Analysis of Restaurant Reviews (NLP Use Case)
User: chandrakant817
countvectorizer,Proteins have different family types, this modal determine a protein's family type based on sequence. Inspired by search engines such as BLAST which has this capability, but it want to try out and see if a machine learning approach can do a good job in classifying a protein's family based on the protein sequence.
User: chey97
countvectorizer,Predicting Tags for Stack Overflow
User: cltai9145
countvectorizer,Multi label classification. Dataset is from Kaggle(https://www.kaggle.com/badalgupta/stack-overflow-tag-prediction)
User: drag97
countvectorizer,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.
User: garg-priya-creator
countvectorizer,This repository is from my own nature_inspired_programming repository. I just decided to make it a separate repository. This is an implementation of custom natural language preprocessing for AutoML library tpot.
User: jayveersinh-raj
countvectorizer,Used spaCy tokenizer to process the text and BeautifulSoap to remove HTML tags from the job descriptions. Built tokenizer and used CountVectorizer to get the word counts for each listing. Created dtm and tf-idf feature matrix. Built search engine to query the job listings and find documents that are similar to the desired job listings.
User: jianninapinto
countvectorizer,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.
User: jugg097
countvectorizer,To what extent a resume is matching a job add requirements, description? What are the most similar applications?
User: kalideir
countvectorizer,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.
User: kawaljeet2001
Home Page: https://movierecsys-ksb.herokuapp.com
countvectorizer,Develop Machine Learning models to predict sentiments on COVID-19 tweets.
User: lensin3
Home Page: https://covid19sentiments.herokuapp.com/
countvectorizer,Can we learn about the Resist Movement by analyzing #resist tweets?
User: lorenaparralanda
countvectorizer,Spam Detection – Cluster SMS messages to “Spam” and “Ham” (Kaggle Challenge)
User: lovpatel93
Home Page: https://www.kaggle.com/uciml/sms-spam-collection-dataset/home
countvectorizer,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.
User: lunaticprakash
countvectorizer,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.
User: mandar196
countvectorizer,Grocery Recommendation on Instacart Data
User: melodygr
countvectorizer,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
User: mingalievdinar
countvectorizer,Build custom vacab, Ham /Spam using tfidf , Movie review classification using TFIDF
User: najiaboo
countvectorizer,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.
User: nandakumarsg
countvectorizer,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.
User: nikhilkr29
countvectorizer,What is the difference between a data scientist and a data analyst? An NLP approach.
User: pleonova
countvectorizer,Text classification using various techniques, including Naive Bayes and Passive Aggressive classifiers, along with different vectorization methods such as Count Vectorization
User: prakriti0501
countvectorizer,A Machine Learning Model that detects different language syntax.
User: rimmelasghar
countvectorizer,Note : This Repository consists files of the NLP Project - Fake News Detection Classifier which was held as a Data Science assessment by Techigai ,Hyd.
User: saivivek7495
countvectorizer,SMS SPAM FILTERING
User: samarth0174
countvectorizer,The aim of this project is to determine the emotion that is associated with a given body of text.
User: selkhayri
countvectorizer,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%.
User: shubhamsharma476
countvectorizer,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.
User: shubhamsharma476
countvectorizer,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.
User: sudhanshublaze
Home Page: https://email-spamclassifier.herokuapp.com
countvectorizer,This Machine learning powered Recommendation Engine suggests Movies for a user based on the user's past intrests by content based filtering. In this ML model the attributes of movies like genres , cast , director , description are taken into consideration while being converted into vector format. The cosine distance is found between the vectors to find the most similar movies based on the user's input . The dataset used is TMDB_5000 Movies dataset. The framework is made using streamlit.
User: sushantlokhande14
countvectorizer,For learning Purposes
User: tamanna18
countvectorizer,Practice Rust by making Vectorizer
User: tangojp
countvectorizer,To put a halt to the distribution of incorrect information from any online news outlet. Build an NLP Classifier that can identify news as Real or Fake.
User: uttej2001
Home Page: https://fakenews-analysis.herokuapp.com
countvectorizer,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
countvectorizer,Named Entity Recognition , Emotion Mining in Python
User: vaitybharati
countvectorizer,linebot messengerbot @mango by fastapi
User: watcharap0n
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