-
University of Illinois
- Illinois, USA
- in/rohit-kaushik4
- https://medium.com/@kaushikrohit4
- https://orcid.org/0000-0001-6578-4641
Stars
Python pathlib-style classes for cloud storage services such as Amazon S3, Azure Blob Storage, and Google Cloud Storage.
A Python package designed to identify 40+ animal species, train custom models, and estimate distances from camera trap videos.
This repository demonstrates how to set up automated model training workflows triggered by AWS S3 using Kestra. When new customer interaction data is added to S3, the system retrains recommendation…
Space Invaders game developed using Pygame
RegrCoeffsExplorer is a tool that enhances the interpretation of regression results by visualizing empirical data distributions. It supports Linear Models (LM), Generalized Linear Models (GLM), and…
The project is a Reddit sentiment analysis tool that identifies trending stock tickers and evaluates community sentiment using the Vader Sentiment Intensity Analyzer.
The Knowledge-Aware Conversational Recommendation System utilizes conversational data from smart devices to predict movie preferences. It analyzes user sentiment and employs collaborative filtering…
This special README repository is a dynamic reflection of me, designed to share my expertise and connect with the community.
A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS
Copyleaks Plagiarism API offers robust and precise plagiarism detection, enabling developers to seamlessly integrate originality checks into their applications for maintaining content integrity.
A breakthrough Convolutional Neural Network (CNN) application that accurately interprets sign language, transforming gestures into speech and text, fostering seamless communication for the deaf com…
In this notebook, my objective is to explore the popular MNIST dataset and build an SVM model to classify handwritten digits. Here is a detailed description of the dataset.