lokeshnahar Goto Github PK

ace_for_sarcasm_detection

predictive model for detecting sarcasm in text passages by combining affective and contextual features. – Leveraged Bi-LSTM model with multi-head attention and EAISe model to capture affective features and Integrated BERT-based Sentence Transformer for contextual embeddings. This innovative fusion led to precisely detect sarcasm

anomaly-detection

Detects Anomaly from a streaming Data

end-to-end-am-streamlit

face_recognition_attendence_system

Project under Microsoft Engage 2022

iitg

image-style-transfer

For a given content image and a style image, the outline and shape of the image are similar to the content image, and the color or texture is changed to be similar to the style image.

movie_recommendor

Movie Recommender System utilizing techniques including Collaborative filtering and SVD in Python

optimization-methods-me609

This repository was a course project under the supervision of Prof. Deepak Sharma at IIT Guwahati. The codes find the optimal point and value for any given function.

query-engine-vector

Implemented vector embeddings on the dataset and store them in Qdrant a vector DB. Implemented LLM on the DB that can give contextual answers to the queries. Wraped this LLM as an API using FastAPI and streamlit frontend

tic-tac-toe

Tic Tac Toe game in python

toxic-comment-classifier

This Repository is a part of Course Project under the guidance of Dr. Ashish Anand at IIT Guwahati, under the course - Introduction to Natural Language Processing.