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

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.

Ngrams with Basic Smoothings

nlpNatural Language Processing MAterial

Ngrams with Basic Smoothings

Advanced techniques for improving performance of Hidden Markov Models

Computer Vision and its application in Autonomous Vehicles

Pure Python implementation of a categorical Naive Bayes classifier from scratch, with a scikit-learn-style `fit`/`predict` API.

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.

This was the course project for Digital Image Processing (CS663), in the Autumn Semester of 2024-25, at IIT Bombay

Ngrams with basic smoothing.

N-gram models- Unsmoothed, Laplace, Deleted Interpolation

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

Ngrams with Basic Smoothings

Builds N-gram language modes and applies text generation.

This is an entire implementation with Good-Turing estimate, MLE, and Laplacian backoff Language Model

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

Distributed and Online Maintenance of Bayesian Networks in Apache Flink

This repository implements an n-gram-based language model for the CS6320 NLP course at UT Dallas, focusing on word sequence prediction, text preprocessing, smoothing techniques, and model evaluation.

🧠 Build an N-gram language model to generate coherent text, predict next words, and evaluate performance with real-world data.

Ranks passages against queries using various models and techniques.

A Multinomial Naive Bayes classifier with Laplace smoothing from scratch for 3-class and 5-class sentiment analysis of movie reviews.

This Project is an implementation of a Naive Bayes Classifier with use of Laplace Smoothing technique.