In this repository, the project on NLP-based chatbot that generates responses based on the command given to the system.

Applying natural language processing to understanding the latest sentiment of news articles featuring Bitcoin and Ethereum.

ML model for rating prediction with NTLK and Scikit-learn.

Una guía rápida para la limpieza de texto usando la biblioteca NLTK

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.

Exploratory Analysis of Amazon Product Reviews Dataset comprising of various categories spanning over 14 years

This is an information retrieval engine running on the shoulders of ntlk library.

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.

Data Science Project for Udacity's Data Scientist Program. Here I created a webapp and ML/NLP pipeline that analyzes message data for disaster response and shows classification results.

Here are some of my projects implemented during the training in Yandex.Practicum

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.

Web scraping product reviews data from AliExpress.

This project involves comprehensive data analysis and application development using a dataset of approximately 160K TV shows.

Spontaneous Poetry Analysis Machine

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).

This project is part of Udacity's Data Scientist Nanodegree. In it, we use natural language processing (NLP) to analyze messages from real-world disasters for categorization.

Introduction to Artificial Intelligence with Python

Using text analytics to understand cultural patterns in philosophical texts. Exploring gender, author, region, and time-period differences, and extracting key philosophical concepts.

An interactive Thesarus that provides real-time word support using nltk and pyperclip

Employs the NLTK library to craft Shakespearean Sonnets