This project is an auto-filling text program implemented in Python using N-gram models. The program suggests the next word based on the input given by the user. It utilizes N-gram models, specifically Trigrams and Bigrams, to generate predictions.

Artificial Intelligence Course 4th Project: Implementing Bigram and Unigram models for filtering comments

AUT Principles and Applications of Artificial Intelligence course (Fall 2020) projects

Drawing inspiration from Andrej Karpathy’s iconic lecture, "Let’s Build GPT: From Scratch, in Code, Spelled Out", this project takes you on an immersive journey into the inner workings of GPT. Step-by-step, we’ll construct a GPT model from the ground up, demystifying its architecture and bringing its mechanics to life through hands-on coding.

Solutions for Andrej Karpathy's "Neural Networks: Zero to Hero" course

It's a python based n-gram langauage model which calculates bigrams, probability and smooth probability (laplace) of a sentence using bi-gram and perplexity of the model.

Natural Language Processing - Part-Of-Speech Tagging

Very simple implementation of GPT architecture using PyTorch and Jupyter.

Advance information retrieval system that combines advanced indexing, machine learning, and personalized search to enhance academic research and document discovery.

Implementation of Handwritten Text Recognition Systems using TensorFlow

This project is meant to generate a Local Language Model based on textual input.

Detection of language of a written text using bigram letter model.

NLP-persian-poet-identification

👨🏻‍💻 My own repository to explore LearnQuran tech product in particular -obviously- AI stuffs

Detect the text language automatically using a bigram model, Support Vector Machines, and Artifical Neural Networks. The model is trained using the WiLI-2018 benchmark dataset, and the highest accuracy achieved on the test dataset is 99.7% with paragraph text.

Final year major project on big data analysis of instacart dataset and finally Product Bundle Recommendation using pyspark(for clustering) and bigram for recommendation

Implementation of lightweight transformer model for character level text generation

First Proper (formal) piece of Java software I created. It focuses on 5 different techniques of scoring documents based on queries. It also includes the code I used on AWS for a bigram model and predictions.

Artifacts for CS-539 Natural Language Processing course