Stempel port to go.

Program that preprocesses a collection of documents to calculate the frequency of the most common terms and identify the keywords of each document. The first time will do it without using the stemming technique and without removing the stopwords. The second time will use these techniques.

Implementation of some famous machine learning algorithm from scratch

Text mining in Python

Jupyter Notebook for Natural Language Processing with Python. Please refer to the README.md file for the topics covered in this Notebook.

A multi-class classification problem where the objective is to read a question posted on the popular reference website, StackOverflow and predict the primary topics it deals with, i.e. tags which the question will be associated with.

To understand the impact on stock price based on the various news headlines.

Extract text content from an HTML page, process it, and extract unique words from the processed text. This notebook utilizes various text processing techniques including cleaning, normalization, tokenization, lemmatization or stemming, and stop words removal.

Gentle introduction to basic elasticsearch constructs boosting search: ngrams, shingles, stemmers, suggesters and fuzzy queries.

Natural language processing for Tamazight language

Educational Document Base prototype to perform queries based on similarity and dissimilarity measures of documents to which stemming, lemmantization and latent semantic indexing was applied.

ML model for Fake news detection

In this project I used different text preprocessing techniques to preprocess my text data. The I used different classification algorithm to get the best results as it was a classification problem. I used Kaggles free GPUs and Datasets in this competion.

classify sentences based on the sentiment they express, emphasizing on long sentences

Spam classifier using NLP

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

Text Processing performed on the Apple Macbook for feature extraction

All Lab assignments of NLP Course covered in IIIT

Resume classification is the task that automatically categorizes resumes or CVs into predefined domain categories or classes based on their content. This task is essential for the job recruitment process, particularly when organizations receive a large number of applications for various positions.