There are 2 repositories under ntlk topic.
A bespoke NLP Chatbot trained using a corpus of Reddit data.
Sentiment analysis on tweets analyzing any trade-able asset (Cryptocurrency) using Machine Learning and statistical classification model
This sentiment analysis API uses Flask-restful and provides a positive or negative sentiment response to input query.
Braggi is a Python based Contextual Chatbot Framework, which hopes to integrate all the necessities for a great chatbot framework, to satisfy both enterprise and general audiences alike. Development still underway, more features on the way 😄
A sentiment analysis and web-sockets application with twitter's streaming api
Not your normal social media market!
This is an information retrieval engine running on the shoulders of ntlk library.
Sentiment analysis, analyzing user’s textual reviews, to perform a binary classification task (positive or negative mood). Designed a machine learning pipeline able to achieve an F1 score of 96.7% on unseen reviews.
This repository contains two Python scripts for Natural Language Processing (NLP) tasks and text summarization, as well as a requirements.txt file specifying the necessary dependencies.
Are you feeling bored? Well never again because! Our little digital friend Sophie is here for you to talk. Ask her questions, tell her about yourself and she will listen and interact with you always.
Exploratory Analysis of Amazon Product Reviews Dataset comprising of various categories spanning over 14 years
This project involves comprehensive data analysis and application development using a dataset of approximately 160K TV shows.
In this study, I utilized the unsupervised approach Kmeans to cluster/group reviews in order to discover major topics/ideas within the sea of text. This applies to all textual evaluations. In this series, I've concentrated on Twitter data of Vodaphone, which is more real-world and sophisticated than evaluations acquired via survey or review forms.
A movie recommender system that uses SBERT for embedding and cosine similarity for recommendations.
Web scraping product reviews data from AliExpress.
In this repository, the project on NLP-based chatbot that generates responses based on the command given to the system.
Bangla Music Mood Detect Pattern Lab Project
Projeto Estágio Supervisionado
The Text Summarizer Web Application utilizes Python, Flask, NLTK, and Bootstrap for creating concise summaries from long texts. No frills, just an efficient tool for simplifying complex content.
A simple search engine built using Python 3.11 that implements TF-IDF weighting, page ranking, and cosine vector similarity, and utilizes NLTK libraries for tokenization and stemming.
Here are some of my projects implemented during the training in Yandex.Practicum
учебные проекты Яндекс.Практикум "Специалист по Data Science"
This repository contains Python code for text classification and analysis of e-commerce sales data. The script processes textual descriptions of products and categorizes them into predefined categories using a Naive Bayes classifier. It also includes various analysis and visualization methods to explore the dataset.
Using text analytics to understand cultural patterns in philosophical texts. Exploring gender, author, region, and time-period differences, and extracting key philosophical concepts.
An implementation of an Information Retrieval System that indexes documents and matches queries using vector space models (Jaccard, Cosine, Scalar), boolean model, and probabilistic model (BM25).
Dobby The-Chatbot is a conversational agent developed as a hobby project while exploring Python's NLTK library. Built using the nltk.chat.util module with Chat and reflections, this chatbot simulates a conversation with users based on predefined patterns and responses.
piores lugares para se estar na TI , worst place to work in Brasil
I developed a Flask application using NLTK and Docker. Within the application, I created a JSON file named intents, which contains various questions and answers. The Chatbot in the application responds to user queries using the data provided in the intents file.
Employs the NLTK library to craft Shakespearean Sonnets
Una guía rápida para la limpieza de texto usando la biblioteca NLTK
For this project, machine learning algorithms are used on amazon fine food reviews dataset to analyze if the given review is a positive review or a negative review.
AutoSubFinder is an innovative coding project that aims to automatically find and download subtitle track files for movies and other videos. The project utilizes web scraping and Natural Language Processing (NLP) techniques to search various subtitle databases and provide accurate and synchronized subtitle tracks for videos.