GitHub topics: nltk-library

Repositories

Keshav25-2002/SMS-spam-detection-using-NLP

The SMS Spam Collection is a set of SMS tagged messages that have been collected for SMS Spam research. It contains one set of SMS messages in English of 5,574 messages, tagged according being ham (legitimate) or spam.

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Keshav25-2002/Text-summarization-using-Word-Frequency

Text Summarization is a very useful technique to get important parts of a large text document. This project uses word frequencies of the sentence and yield a score for each sentence.

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samagra44/SMS-Spam-Classifier

This project is designed to classify emails as either spam or legitimate using machine learning techniques and natural language processing (NLP).

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amal-krishna-m-u/SignLanguageDetection

This is a website which help differently abled personals communicate.It can detect sign Languages gestures and also generate signlange gestures

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AjNavneet/TextClassification_LogisticRegression_AppReviews

Basic text preprocessing and a text classification model using logistic regression for App reviews data.

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sherirosalia/cupid_shuffle

What sings to your heart, country or hip hop? Python, NLTK, NLP, applied to analyzing lyrics.

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balaji1233/youtube-comment-sentiment-Insights

This project delivers a robust web application that conducts potent sentiment analysis on YouTube comments.

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Mythamor/Tazama-A-Django-Movie-Recommendation-Web-App

Tazama is a movie recommendation web app built with Django. It also features a mini-blog to add a social touch to the platform

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Aman83770/Briefly

A Text Summerization web app made on Flask framework

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elmezianech/ClassifyReviews_NLP

Revolutionize customer feedback analysis with our NLP Insights Analyzer. Utilize cutting-edge text preprocessing to transform raw reviews into a machine-friendly format. Explore sentiment models, such as Logistic Regression and Naive Bayes, employing cross-validation for model robustness.

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rishitbhojak/HASOC_2021

HASOC 2021 NLP Project Repo

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manena/sp-sentiment-analysis

Sentiment Analysis in Python trained with Amazon Spain reviews in Spanish

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FarhanaTeli/Sentiment_Analysis_IMDB

The comparison between different embeddings (TF-IDF, USE, and TF-IDF + USE) and various classifiers provides valuable insights into the performance of different techniques for sentiment classification.

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Netcodez/NLP-and-Clustering---Movie-similarity

Using NLP and Clustering on movie plot summaries from IMDB and Wikipedia to quantify movie similarity

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vidhi-ambwani/Amazon-Customer-Review

Sentiment analysis on Amazon customer reviews and analyzing customer behavior using NLTK and wordclouds

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suvrashaw/CureTalk

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suneelpatel/Natural-Language-Processing-NLP

This repository will provide an overview and working knowledge of Natural Language Processing (NLP), using Python’s Natural Language Toolkit (NLTK) library and with Keras.

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Kunal-Kumar-Das191049/Sentimental-Analysis-of-Amazon-Reviews

The Amazon Review Sentiment Analysis project is a machine learning project that aims to classify the sentiment of Amazon customer reviews using Natural Language Toolkit's VADER sentiment analysis tool and the huggingface Roberta Transformers package.

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aayush210789/Sentiment-Analysis

Sentiment Analysis of Movie reviews

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divyansh1195/Natural-Language-Processing

NLP Projects Implementation.

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RAVI-CHANDRIKA-05/ANALYSING_DISNEYLAND_REVIEWS_NLP

this repo contains files for my analysis on disney land visitor reviews using NLP

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Anshul21107/SMS-Spam-Classifier

SMS Spam Classifier is a machine learning project that classifies SMS messages as either spam or not spam (ham).

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3sarojbhattarai/project_nlp

Explaining different Natural Language Processing Libraries such as nltk and word2vec with coding. There are also some examples of nlp such as text summarization, text classification and sentiment Analysis.

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jegazhu/text-sentiment-python

This is about sentiment text analysis in Python. I used libraries that allow us to work with natural language processing

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MaaMachado/chatbot

Atividade Final de Python - Construir um ChatBot para atendimento ao cliente

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caciitg/UTrack

UTrack analyses the user's tweets and finds the level of Loneliness, Stress and Anxiety, and their trends over time

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ISAIAH-Git/Translating_English_Phrases_to_FRENCH_Phrases

TRANSLATING ENGLISH PHRASES TO FRENCH PHRASES

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YangLei2586/Python_Sentiment_Analysis_with_nltk

A simple Naive Bayes Classifier for sentiment analysis sample built on nltk

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gurvinder08/Amazon-Alexa-Reviews-Sentiment-Analysis

Sentiment Analysis of the customer reviews for Amazon Alexa. The dataset used was downloaded from Kaggle.

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ACallglad/sentiment-analysis-of-humans

This project can be widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.

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infokiftikhar/Python-based-Sentiment-Analysis-with-Graphical-User-Interface-GUI-

Sentiment Analysis on Movie Review file with Python with the help of some common Python libraries i.e nltk, textblob, gensim etc. Also GUI is added in the Project with Python Tkinter Library.

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Gokultcr/NLP-20newsgroup-data

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Ghaithkrifa/jobs-analysis

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GOUTHAM1921/NLP---SENTIMENT-ANALYSIS

A NLP Project related to Sentiment Analysis. Deriving the sentiment from the reviews made by the Amazon customers on a product.

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PeterSchuld/Disaster-Response-Pipeline-

Project No.2 (Data Engineering) in the Data Scientist Nanodegree program. Build a machine learning pipeline to categorize emergency messages based on the need communicated by the sender.

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mansourshebli/nltkPython

In this repo I provided simple examples to demonstrate how the the fundamentals of NLP on the NLTK library in Python works; Tokenization, Stopword Removal, Parts of Speech Tagging, Named Entity Recognition, Sentiment Analysis using VADER. For better understanding check this NLTK documentation:

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Chandrakant817/NLP-Notes-with-Implementation

NLP Hand Written Notes

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zuzannna/CoffeeFlavors

☕ Automatic tagging for coffee reviews using SCAA flavor wheel standardized tags 🤖☕

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shilpavijay/NLTK-know-how

NLTK libraries and Machine Learning Algorithms in use.

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BashMocha/cs50-ai

Project submissions for Harvard CS50's Introduction to Artificial Intelligence with Python

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nilmolne/Text-Mining-The-New-York-Times-Articles

Provides the tools needed to mine text from The New York Times online articles by using Python and a dictionary text mining technique, given a time range and country of interest.

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vishalpallerla/Gender-Identification

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felipexw/guessb

Webapp para classificar comentários (positivos, negativos e neutros) advindos do Facebook usando Natural Language Toolkit (NLTK) + Django e Bootstrap na interface Web.

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Tomjg14/Reddit-crawler

This repository is on the collection of comments from Reddit and how to work with those comments to perform sentiment analysis.

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tarunsinghal92/course_resdesign_ds

Course Curriculum redesign using Data Science & Analytics

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antrad1978/SentimentAnalysis

PySpark Sentiment Analysis with NLTK and Kafka

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Akhileshkumarkc/Natural-Language-Processing

NLP Related Projects including Lesk implementation, Viterbi Algorithm, Sentence Probability Calculation - Monogram,Bi gram, Tri Gram(with and without Smoothing)

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tohid-yousefi/Sentiment_Analysis_on_Amazon_Kozmos_Reviews

In this section, we will do a sentiment analysis on amazon kozmos product reviews.

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alicediakova/Lexical-Substitution

Project for Natural Language Processing Course at Columbia University's School of Engineering and Applied Science, Nov 2022

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tohid-yousefi/Sentiment_Analysis_on_Amazon_Product_Reviews

In this section, we will do a sentiment analysis on amazon product reviews.

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ridhimanamdev/Sentiment_Analysis

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silveirinhajuan/juanprime

I need help to improve my model and database. JuanPrime is a machine learning project built with PyTorch, focusing on creating a Discord bot. It utilizes natural language processing techniques to provide interactive bot functionalities within the Discord platform.

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MeqdadDev/articles-text-to-speech

Convert the text of articles to speech using nltk, newspaper and gTTS with Python.

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Bavhead/SearchEngine

A command line based local search engine.

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shruti-2412/SMS-Spam-Classifier

Predicting where a SMS or Email is spam or not

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Anderson-Andre-P/Summary-Generator-With-Python-and-NLTK

This algorithm was developed in Python using the NLTK library, it is capable of generating a summary from a given text.

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Abhi-gits/auto-correct-app

Auto correct app is a machine learning and NLP based project. It uses python and nltk library.

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Owzok/SPIMI-Info-Retrieval

Databases 2 - Project 2: Single-Pass In-Memory Indexing for information search and recovery

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snehamanasa/ChatBot

ChatBot trained on the dataset uses deep learning techniques such as LSTMs to classify which category the user’s message belongs to.

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S4tvik/WhatsApp-Analytics

Whatsapp group chat analysis

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AhmedAbdAlkreem/Grammer-Auto-Correct

In this project work to make classification between the phase is correct or wrong if phase is right print the correct phase if phase is wrong be input of Transfer Learning and print the phase begore correct.

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datalivre/web-scraping

Raspando o site www.letras.mus.br em busca de letras musicais (scraping e crawling).

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VIKINGS03/Public_Stock_Sentiment_Analysis

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AshiniAnantharaman/Classification_of_Refactoring_Types

This is a Natural Language Processing project which is used to classify the 6 method level refactoring types from the commit messges in github

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anayaml/nltk-sentences

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Shubha23/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.

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Wiryco/Natural-Language-Analysis-And-Processing

Estudo sobre análise e processamento de linguagem natural usando a biblioteca NLTK

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su050300/webster2020 Fork of harshit212705/StrangeFlix

An On-Demand Video Streaming platform that provides an immersive experience where users can watch all their favorite movies, series, and videos.

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Shakilgithub20/Improving-Classification

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aifenaike/Customer-Review-Sentiment-Analysis

A sentiment analysis model for food product reviews by customers.

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prashant-kikani/Sarcasm-detector

Sarcastic sentence detector. Trained by sarcastic tweets.

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abhishek305/PyBot-A-ChatBot-For-Answering-Python-Queries-Using-NLP

Pybot can change the way learners try to learn python programming language in a more interactive way. This chatbot will try to solve or provide answer to almost every python related issues or queries that the user is asking for. We are implementing NLP for improving the efficiency of the chatbot. We will include voice feature for more interactivity to the user. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation. NLTK has been called “a wonderful tool for teaching and working in, computational linguistics using Python,” and “an amazing library to play with natural language.The main issue with text data is that it is all in text format (strings). However, the Machine learning algorithms need some sort of numerical feature vector in order to perform the task. So before we start with any NLP project we need to pre-process it to make it ideal for working. Converting the entire text into uppercase or lowercase, so that the algorithm does not treat the same words in different cases as different Tokenization is just the term used to describe the process of converting the normal text strings into a list of tokens i.e words that we actually want. Sentence tokenizer can be used to find the list of sentences and Word tokenizer can be used to find the list of words in strings.Removing Noise i.e everything that isn’t in a standard number or letter.Removing Stop words. Sometimes, some extremely common words which would appear to be of little value in helping select documents matching a user need are excluded from the vocabulary entirely. These words are called stop words.Stemming is the process of reducing inflected (or sometimes derived) words to their stem, base or root form — generally a written word form. Example if we were to stem the following words: “Stems”, “Stemming”, “Stemmed”, “and Stemtization”, the result would be a single word “stem”. A slight variant of stemming is lemmatization. The major difference between these is, that, stemming can often create non-existent words, whereas lemmas are actual words. So, your root stem, meaning the word you end up with, is not something you can just look up in a dictionary, but you can look up a lemma. Examples of Lemmatization are that “run” is a base form for words like “running” or “ran” or that the word “better” and “good” are in the same lemma so they are considered the same.

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