Classifying the Blur and Clear Images

Python implementation of an N-gram language model with Laplace smoothing and sentence generation.

A Python implementation of Naive Bayes from scratch.

Ngrams with Basic Smoothings

Word embeddings from PPMI-weighted and dirichlet-smoothed co-occurrence matrices

Adding Noise Noise Canceling Image resizing Resolution Study Filtering processes -Midic filter -Mean filter -Laplasian filter Photo Sharpening

Ngrams with Basic Smoothings

nlpNatural Language Processing MAterial

Ngrams with Basic Smoothings

Ngrams with Basic Smoothings

Tools for navigationally safe bathymetric surface processing - Rolling Coin algorithm, iterative Laplacian smoothing, shoal buffering and surface offsetting. Efficient implementations written in C. Simple command-line interface to support scripting use.

Advanced techniques for improving performance of Hidden Markov Models

Computer Vision and its application in Autonomous Vehicles

This project implements N-Gram (with Laplace Smoothing), LSTM, and Transformer-based models to predict DNA sequences. It evaluates model performance using perplexity scores and explores deep learning approaches for bioinformatics.

A basic application with necessary steps for filtering spam messages using bigram model with python language.

Ngrams with basic smoothing.

Builds N-gram language modes and applies text generation.

Ngrams with Basic Smoothings

An implementation of a Naive Bayes Classifier for predicting Hafez and Saadi poems

Information retrieval system that gives ranked results when a query is given