Text mining in Python

Python implementation of a web crawler that, from a set of seed urls, retrieves the most similar pages.

Transcribes a youtube playlist to tokens and gives you the option to search entire phrases giving you the exact second it appears. 1 Hour playlist = 1 Minute processing.

Customer sentiment analysis is the process of using natural language processing (NLP) and machine learning techniques to analyze and understand the feelings, opinions, and attitudes expressed by customers in textual data, such as reviews, feedback, and social media posts.

Long english text passages are given, a genuine topic is needed to be assigned to the particular text passage. After cleaning the dataset, features were learnt using thidf approach, Linear SVC is used to get the final prediction

Simple Python Implementation of Stemmer and Lemmatizer

Text preprocessing, indexer constructions, and search engines implementation for information retrieval. Performance analysis done by measuring the construction time of indexers.

AI Chatbot using Deep Learning and Natural Language Processing

Information retrieval from basic concepts (tokenization, stop word removal, stemming, TF-IDF, etc.)

Laboratory 2 - Retrieval Information

Tokenization, Stemming, Lemmatization, Bag of words, TF-IDF

This is the basics of Natural Language Processing with NLTK python library. I have used Bag of words and TF IDF techniques for word vectorization for the machine learning model to train the model on. Before applying techniques I have used Stemming and Lemmatization on text data to transform text data into meaningful important words. Of course Le…

Simple chatbot with machine learning NLP model to answer simple questions and inventory queries.

Data Mining, Clustering and Classification

pre-project indexing document

Data Pre-processing Application/UI is a simple UI which can automate repitive tasks, while ensuring consistency and efficiency in NLP data preprocessing.

Sentiment Analysis on top super smash bros melee players tweets

Web Application for Counting Words in a Document