The uploaded codes help to classify emails into spam and non spam classes by using Support Vector Machine classifier.

Plotly-Dash NLP project. Document similarity measure using Latent Dirichlet Allocation, principal component analysis and finally follow with KMeans clustering. Project is completed with dynamic visual interaction.

Bangla NLP toolkit.

A python package to be used in removing stopwords in different languages.

Created a Python library specifically for Traditional Chinese stopwords and punctuations removal

This Python code retrieves thousands of tweets, classifies them using TextBlob and VADER in tandem, summarizes each classification using LexRank, Luhn, LSA, and LSA with stopwords, and then ranks stopwords-scrubbed keywords per classification.

K-means clustering of texts (survey answers) using word-embeddings, finding optimal elbow-point, and averaging multiple-word expressions.

Basics of Natural Language Processing

Python package that makes it easy to use stop words lists in Python projects.

50 public profile PDFs from LinkedIn , converting to text then finding most frequent and essential words

Prints contents of file after filtering out stopwords.

Laboratory 2 - Retrieval Information

Implementation of Boolean Search Retrieval model on the 20 Newsgroups Data Set

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

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

Laboratory 3 - Retrieval Information